Data Scientist Marketing Measurement And Attribution

About Daily Harvest
At Daily Harvest we take care of food, so food can take care of you. We're committed to helping you nourish your body while taking care of the planet. How? By making it easy to eat more real, unrefined and sustainably sourced fruits and vegetables every day.  Our team is collaborative, driven, and future-thinking.  We're constantly learning, experimenting, and iterating, and celebrate failure just as much as success. We take risks, try new things, and we get things done. We love adaptogens and cruciferous vegetables but never say no to cake. Everything we do, we do in the service of our community.
Position Overview
Daily Harvest is looking for a Data Scientist to join our Data team. The Data team uses data to create better customer experiences, enable smarter business decisions, and drive innovations company-wide. You will build sophisticated data products and develop machine learning models that strengthen our competitive advantage.
In this role, you’ll work with a modern data stack including GCP / Bigquery, Fivetran, dbt, Airflow and Segment. You’ll support the growth and lifecycle strategy by analyzing tough marketing problems, build and ship models that enable high-quality decision making. You will be a valued thought partner, helping the business define and implement the best approaches to drive marketing decisions as we create a new category and the next great consumer brand in food. This is a highly visible role that has the opportunity to make a big impact on the business.
What you’ll do:

Lead the relationship with key partners on our Marketing teams including Brand, Growth and Lifecycle Marketing to build awareness, increase acquisition, and improve retention with data products
Develop, maintain and improve statistical and machine learning models to drive company’s marketing decisions
Develop forecasting and spend optimization practices to advance our marketing measurement and planning capabilities for the company’s budget cycles
Design and measure marketing experiments to determine the impact of marketing efforts
Dive into marketing channels (Social, Search, Email, and TV, etc.) to further scale and optimize our portfolio
Communicate effectively with both technical and non-technical cross-functional partners

Who you are:

3+ years of building statistical and machine learning models for marketing
Master’s degree (or equivalent practical experience) in Statistics, Computer Science, Engineering, or Mathematics, or related quantitative discipline -- PhD a plus
Strong Python and SQL background
Extensive experience with model development, evaluation and experimentation (specific areas of highly relevant concepts include Bayesian statistics, multilevel and generalized linear models, time series forecasting, markov chain attribution, budget optimization)
Experience using PyMC3 or any other Bayesian modeling framework is a huge plus
Experience with media mix optimization and attribution models
Strong understanding of web tracking and digital marketing
Excellent communication skills, including data visualization
Ability to thrive in an unstructured, fast-moving and constantly evolving hyper-growth environment
Passion for research and curiosity that calls you to go beyond “good enough” to create something innovative and exciting
E-commerce experience, especially within a subscription company is a plus

Benefits:

Unlimited PTO Plan + flexible working hours
Equity participation + 401K
Competitive medical, dental, + vision insurance
Fun IRL + virtual quarterly team events, happy hours, + DH team gatherings to celebrate our co-workers
Ancillary benefits: Commuter, Citi Bike discounts, + Health & Wellness Perks
Annual company retreat
Unlimited Daily Harvest in the office to keep you hustling, not hangry (...always stocked)
In office access to everything we create (including recipes in development)

At Daily Harvest, our mission is to take care of food, so that food can take care of you. And it wouldn't be possible without our team. We celebrate the unique POV that each person brings to the table and believe in a collaborative and inclusive environment. As an equal opportunity employer, we prohibit any unlawful discrimination on the basis of race, color, religion, military or veteran status, sex, gender, gender identity or expression, sexual orientation, national origin, age, disability or genetic information. These are our guiding principles and apply across all aspects of employment.


Sr Data Scientist Ads Machine Learning

We are looking for a Senior Machine Learning Data Scientist to join the Ads Quality team. You will work closely with engineers and product owners to 1) set up the vision and product strategy of ads quality and relevance, 2) optimize ads delivery and auction systems through utility function design, 3) measure various marketplace tradeoffs. This person possesses a solid technical background, strong business acumen, and excellent cross-functional stakeholders management skills.
Reddit is continuing to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.
Responsibilities:

Research, design and develop contextual ad relevance models. Reddit ads are a combination of text, image, user and ad engagement attributes. You will use modern deep learning techniques to combine those signals to measure ad quality.
You will design metrics and mechanisms to understand different tradeoffs between user engagement and ad quality. You will develop algorithms that would optimize both ad quality and ad delivery.
Be involved in all phases of modeling such as ideation, offline modeling, online implementation, experimentation, deploy and post-launch monitoring/measurements.
This role will have a lot of overlap with other Machine Learning Engineer roles, but will differ in a couple of areas. First is that you will work mainly on offline modeling and rely on engineers to productionize your models. Secondly, you will have a keen interest in the collection and quality of underlying data (experiment design and analysis, data deep dive), along with working on ETLs and data aggregations needed for training, testing and productionizing models.
Serve as a thought-partner for product managers, engineering managers and leadership in shaping the monetization roadmap and strategy for Reddit by identifying opportunities through deep-dive analyses and/or modeling.

What We Can Expect From You:

Bachelor’s degree or above in Mathematics, Statistics, Machine Learning, Computer Science, Economics, or other quantitative fields
Master’s or PhD degree is preferred but not required
Proficiency in machine learning, statistical modeling, and optimization
Understanding of experimentation and causal inference analyses
Strong analytical and communication skills
Familiarity with at least one of the Deep Learning platforms (e.g. Pytorch, Tensorflow)
Computer vision experience strongly preferred
Strong skills in SQL and programming (Python or R)


Senior Marketing Data Scientist

Rec Room is the best place to build and play games together. Chat, hang out, explore MILLIONS of rooms, or build something new to share with us all!
Rec Room continues to grow quickly (640% year over year on mobile!), thanks to the great product and our experienced marketing team. As the Senior Marketing Data Scientist, you’ll work closely with the Growth org to build out our foundational data sets and add a higher level of sophistication to our marketing analytics. You’ll think through developing our in-house methodology for evaluating marketing efficiency, providing visibility into previously difficult-to-understand channels, and helping us acquire users that are best for the business.
You’ll be joining the quickly growing Data team, composed of Analytics Engineers and Product Data Scientists, and work off an entirely modern infra. The team is focused on driving impact through the product, and as the Marketing DS, you’ll have the opportunity to define our growth strategy.
WHAT YOU'LL DO:

Work collaboratively across functions, regularly interfacing with the Marketing, Product Growth, and the Creator teams to optimize our marketing spend and outreach programs
Partner with marketing leadership in strategy development, goal setting, and budget planning
Provide end-to-end campaign support, spanning from pre-campaign goal setting and measurement plan development, to in-campaign performance insights and optimization recommendations, to post-campaign evaluation and lessons learned
Provide strategic guidance by identifying predictive behavioral patterns that result in high-value users
Lead experimental design for A/B tests across platforms
Work with the events and creators team to define programs and incentives that can grow our userbase amongst key cohorts
Own our LTV model that powers our marketing spend and decision making
Work closely with our Analytics Engineering team to define some of our most important metrics, and build out the datasets that can power our next phase of data-driven marketing
Develop and improve our performance marketing reporting platform

WE ARE LOOKING FOR INDIVIDUALS WITH:

5+ years of marketing analytics experience, with a proven track record of deriving insights that lead to significant marketing budget reallocation
A Bachelor’s or Master’s in Math, CS, or related field
Very strong knowledge of SQL
Experience with Python or R is a plus
Experience with media mix modeling a plus
Experience with gaming LTVs a plus
Effective communicator with the ability to distill complex concepts into easily digestible insights
Adept in visualization tools such as Tableau or Looker

COMPANY INFO TO KNOW:
Rec Room offers generous medical, dental, and vision plans that cover you, your spouse/domestic partner, and children. We also support your retirement benefits with a company match. Rec Room values work-life balance by providing unlimited paid time off. Our company values are real and drive our culture. We work hard to be a safe and friendly place for people from all walks of life.
Rec Room provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.


Data Scientist Senior

Position Overview
At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Data Scientist within PNC's Retail Lending organization, you will be based within the PNC footprint. This is a remote position that can sit within the PNC footprint, although it may not be available in all jurisdictions.
In this role you will:•	Join a team of data scientists and engineers, in collaboration with product managers to uncover and prevent complex fraudulent activity within a wide variety of products and channels•	Utilize a wide array of technologies such as Python, PySpark, Tableau, Neo4j and others to identify anomalous patterns within large amounts of transactional data •	Build and implement traditional and machine learning models (Logistic Regression, XGBoost, Random Forest, Collaborative Filtering, Neural Networks, etc.) models from inception to implementation, while collaborating with product managers and business leaders to drive fraud objectives
Preferred Qualifications:•	Experience in data mining/exploration in banking or similar industries, with an emphasis on large data and effectively communicate insights and results•	Knowledge of statistically modeling and analytical techniques (supervised, unsupervised, clustering, classification, etc.)•	Comfortable with a team-based project structure, with experience in code collaboration tools such as Git and JIRA focused on developing modular, readable, and adaptable code •	Strong understanding of data engineering, with the ability to transform raw data into robust features as input to machine learning algorithms
Job Description
Leads the implementation of analytical projects that leverage vast amounts of structured and unstructured data to extract actionable business insights.Directs the data gathering, data processing and data mining of large and complex datasets.Leads the development of algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.Leads analytical experiments in a methodical manner to find opportunities for product and process optimization. Presents business insights to management using visualization technologies and data storytelling.Partners with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.
PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:
Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.
Competencies
Data Architecture – Knowledge and ability to create models and standards to govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations.Data Mining – Knowledge of tools, techniques and practices in data mining technologies used to acquire essential business information.Disruptive Innovation – Knowledge of concepts, principles, and approaches of disruptive innovation; ability to adopt the knowledge into related processes and practices.Information Capture – Knowledge of the processes and the ability to identify, capture and document relevant business information in an auditable, organized, understandable and easily retrievable manner.Machine Learning – Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.Modeling: Data, Process, Events, Objects – Knowledge of and the ability to use tools and techniques for analyzing and documenting logical relationships among data, processes or events.Prototyping – Knowledge of and ability to implement prototyping disciplines, tools and techniques in evolutionary models within the target environment.Query and Database Access Tools – Knowledge of and the ability to use, support and access facilities for extracting and formatting a database management system.
Work Experience
Roles at this level typically require a university / college degree, with 5+ years of industry-relevant experience. Specific certifications are often required. In lieu of a degree, a comparable combination of education and experience (including military service) may be considered.
Education
Masters
Additional Job Description
Base salary: commensurate with skills and experience
Benefits
PNC offers employees a comprehensive range of benefits to help meet your needs now and in the future. Depending on your eligibility, options for full-time employees include medical/prescription drug coverage (with a Health Savings Account feature); dental and vision options; employee and spouse/child life insurance; short- and long-term disability protection; maternity and parental leave; paid holidays, vacation days and occasional absence time; 401(k), pension and stock purchase plans; dependent care reimbursement account; back-up child/elder care; adoption assistance; educational assistance and a robust wellness program with financial incentives. To learn more about these and other programs, including benefits for part-time employees, visit pncbenefits.com > New to PNC.
Disability Accommodations Statement:
The PNC workplace is inclusive and supportive of individual needs. If you have a physical or other impairment that might require an accommodation, including technical assistance with the PNC Careers website or submission process, please call 877-968-7762 and select Option 4: Recruiting or contact us via email at pathfinder@pnc.com.
The Human Resources Service Center hours of operation are Monday - Friday 9:00 AM to 5:00 PM ET.
Equal Employment Opportunity (EEO):
PNC provides equal employment opportunity to qualified persons regardless of race, color, sex, religion, national origin, age, sexual orientation, gender identity, disability, veteran status, or other categories protected by law.
California Residents
Refer to the California Consumer Privacy Act Privacy Notice to gain understanding of how PNC may use or disclose your personal information in our hiring practices.


Data Scientist Analytics Trust Safety

About Us
Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It’s where millions of people come together to chat, interact, and make their own entertainment.
We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and Twitter, get interviewing tips on Instagram, and discover projects we’re solving on our Blog.
About the Role
Data is central to Twitch's decision-making process, and data scientists are a critical component to evangelize data-driven decision making in all of our operations. As a data scientist at Twitch, you will be on the ground floor with the team, shaping the way we build and refine operational processes, measure the efficacy of policy and deliver insights about safety that influence the way Twitch products are built. You will define what questions should be asked, and scale analytics methods and tools to support our growing business, leading the way for high quality, high velocity decisions for your team.
For this role, we're looking for a data scientist who will assist our Trust & Safety team, with a heavy focus on forecasting and planning to assist operational excellence. The Trust & Safety team's mission is to make Twitch the trusted place for creators to build thriving communities. Your role on the team is to level up the understanding and capabilities of Trust & Safety stakeholders and guide them towards better decision making from the available data. In a typical week or month, you will be responsible for data instrumentation, dashboard/report building, metrics reviews, and ad hoc analysis.
This position can be based in San Francisco, CA or remotely across the US.
You Will:
Own one or more safety data verticals end to end; drive workstreams including data pipelining, data analysis, metric definition, dashboard building and data visualization.
Design and deploy end-to-end process and best practice tooling standards for forecasting and demand planning.
Own and improve demand planning KPIs on forecast accuracy by leveraging historical data and understanding upcoming policy and product changes
Cultivate relationships with cross-functional partners across operations, product, policy, and engineering to remove roadblocks, provide insight, and execute on high-impact projects to reduce harm to the Twitch community.
Prioritize and execute in the face of ambiguity: work with stakeholders and mentors to distill the problem, adapt your tools to answer complicated questions, and identify the trade-offs between speed and quality of different approaches.
Create analytical frameworks to measure team success: partner with cross-functional teams to define success metrics, create approaches to track the data and troubleshoot errors, quantify and evaluate the data, then develop a common language for all colleagues to understand these KPIs.
Operationalize data processes - provide the team with ad-hoc analysis, automated dashboards, and self-service reporting tools so that everyone gets a good sense of the state of the business.
Work with product and engineering teams to build and maintain our data infrastructure to ensure the ability to use data to turn into insights.
You Have:
3+ years of operations planning, demand planning, or forecasting experience
3+ years of industry experience in a relevant field
Bonus Points
Knowledge of demand modeling (e.g., forecasting, planning, optimization etc. and its application to solve real-world staffing problems)
Experience with model building using regression, forecasting, time series, classification, cluster, etc. Experience with quantitative analysis and hypothesis testing
Strong technical data skills including experience with a SQL dialect and experience building tools and automation to clean, transform, merge, and visualize data in a procedural language
Experience with data analysis and visualization tools (SQL, Tableau, Mode, Looker). Programming language skills with R/Python, Statistics or mathematics tools like R, MATLAB, SAS
Proven track record of using data to generate insight and drive business results
Effective written and verbal communication skills to justify forecasting plans to influence peers and executives.
Comfortable working independently; strong prioritization skills and demonstrated ability to manage stakeholder expectations
Must be comfortable working with highly sensitive and/or disturbing content
Perks
Medical, Dental, Vision & Disability Insurance
401(k)
Maternity & Parental Leave
Flexible PTO
Amazon Employee Discount
Monthly Contribution & Discounts for Wellness Related Activities & Programs (e.g., gym memberships, off-site massages, etc.)
We are an equal opportunity employer and value diversity at Twitch. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
The base pay range for this position in Colorado, Connecticut, Washington and New Jersey is $144,000 - $176,000 yr and in New York City is $162,360 - $198,440 yr. Pay is based on market location and may vary depending on job-related knowledge, skills, and experience. A sign-on payment and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via Twitch's internal or external careers site.
Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.
Twitch values your privacy. Please consult our Candidate Privacy Notice, for information about how we collect, use, and disclose personal information of our candidates.
Job ID: TW7772


Senior Data Scientist

Apply Now
How to Apply
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
Note: Remote or Hybrid work arrangement options are available for this position
Summary
Are you wicked smart? Do outer joins and random forests make you giddy like when you were a kid at the toy store? Do we ever have a position for you! We are in search of a Senior Data Scientist/Machine Learning (ML) Specialist to develop predictive analytics that will help improve the treatment of patients in critical care areas such as neurologic emergencies, sepsis, cardiac arrest, and combat casualty care.
This position offers a unique opportunity in the areas of data science and analytics at the Weil Institute For Critical Care Research and Innovation within Michigan Medicine’s Department of Emergency Medicine. Research in our institute focuses on developing clinical decision support systems and a real-time analytics platform for developing and translating advanced data science into critical care.
We are looking for an ambitious, talented, and self-motivated individual with an interest in solving problems as an analytical thinker. Therefore, the candidate is expected to be a dynamic problem solver who is not afraid to “fail fast” as we look to develop the best analytics possible.
This role requires active collaboration with our Data Science team as well as with other clinical collaborators within the school and in other institutes. This collaboration will include requirements gathering to ensure we fully understand exactly what “done” looks like before we start the development of a project.
Who We Are
The Weil Institute Overview
The Weil Institute at the University of Michigan is one of the world’s first comprehensive research enterprises devoted to transforming critical care medicine by accelerating science and moving it from bench to bedside. To do this, the Weil Institute brings together integrative teams of world-class U-M scientists, clinicians, and engineers with industry partners and funding sources to develop and deploy cutting-edge solutions that elevate the care, outcomes, and quality of life of critically ill and injured patients and their families.
Responsibilities*
Additional responsibilities include:
Lead the design, development, and delivery of cutting edge machine learning algorithms Identify data sets needed to develop analytics through consultation and collaboration with faculty, researchers, clinicians, and team members. Translate customer use case requirements into Weil solution designs, demos, and project proposals Communicate clearly and consult with our multi-disciplinary team of scientists, developers, and clinicians. Be an expert on the latest machine learning techniques, methods, and research, and how each of these apply to our use cases Ability to manage multiple projects and assignments with a high level of autonomy and accountability for results
Required Qualifications*
In additional to the above requirements, candidates must also possess the following qualifications:
Masters Degree in Engineering, Computer Science, Applied Mathematics, Statistics, Data Analytics, Health Informatics, or equivalent experience Demonstrated technical knowledge of commonly used data science Python packages including numpy, pandas, and scikit-learn. Proficiency using relevant tools (Python, R, MATLAB, SQL Server, MySQL) Willingness to learn and quickly adjust to new tools and systems Capable of converting ambiguous problem statements into concrete project requirements Passion for data-driven results and customer initiatives Excellent verbal and written communication skills including the ability to communicate effectively and professionally with colleagues and stakeholders. Ability to understand and explain technical concepts to non-technical stakeholders. Confident teaching and coaching abilities
Work Locations
Location
Our office is located on the University of Michigan campus in Ann Arbor, Michigan. This position is open to candidates who are seeking remote and/or hybrid location flexibility.
Background Screening
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.  Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
Application Deadline
Job openings are posted for a minimum of seven calendar days.  The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.
U-M COVID-19 Vaccination Policy
COVID-19 vaccinations, including one booster when eligible, are required for all University of Michigan students, faculty and staff across all campuses, including Michigan Medicine.  This includes those working remotely and temporary workers.   More information on this new policy is available on the U-M Health Response website or the UM-Dearborn and UM-Flint websites.


Data Scientist I

The Data Scientist works with the Product and Data teams to clean, organize, and analyze large volumes of data and produce innovative models, datasets, and visualizations that address our clients’ most pressing problems about the future of work.

Major Responsibilities:

Use SQL, Python, or other related analytical tools and programming languages to query, organize, clean, and analyze large datasets.
Build pragmatic, scalable, and statistically rigorous solutions to large-scale labor market data problems by leveraging or developing state-of-the-art statistical and machine learning methodologies on top of Lightcast's data infrastructure.
Support product development by performing quantitative analysis using Lightcast’s world-class demand and supply data, as well as other data sources to investigate, manipulate, and model solutions for products.
Work cross-functionally to define problem statements, collect data, build analytical models and make recommendations.
Communicate key insights and recommendations to internal and external stakeholders across the organization.
Develop innovative analytical models and document the methodology and findings in a manner accessible to a variety of audiences.
Contribute to positive team culture by participating in team-building activities and being a supportive and empathetic colleague.
Perform other duties as assigned.

Education and Experience:

1 - 3 years of industry or graduate research experience solving analytical problems and building models using quantitative, statistical or machine learning approaches.
Bachelor's degree in Data Science, or a field with a strong quantitative and analytic focus such as Computer Science, Engineering, Mathematics, Statistics, Operations Research, or other related field.

Lightcast is a global leader in labor market insights with headquarters in Moscow (ID) and Boston (MA) and offices in the United Kingdom, Europe, and India.  We work with partners across six continents to help drive economic prosperity and mobility by providing the insights needed to build and develop our people, our institutions and companies, and our communities.

Lightcast is proud to be an equal opportunity workplace and is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Lightcast has always been, and always will be, committed to diversity, equity and inclusion. We seek dynamic professionals from all backgrounds to join our teams, and we encourage our employees to bring their authentic, original, and best selves to work.

#LI-Remote


Data Scientist

A Data Scientist at Lightcast works with the Product, Data, and Classifiers & Extractors teams to produce state-of-the-art models and enriched datasets that address our customers’ most pressing problems about the future of work. A successful candidate will have a strong knowledge of current NLP capabilities, and be comfortable working with big data to build high performance text-based models.

Responsibilities:

Assist in the development of new and existing classification models that process billions of documents at a time.
Research methods to expand, augment, and enhance labeled datasets.
Work closely with Classifiers and Extractors engineering team and Data Engineering team to integrate models and deliver to production environments.
Work with and manage very large (and messy) data sets; build ML pipelines that scale to work with this data effectively.
Perform statistical analysis to understand model performance.

Knowledge, Skills, Abilities:

Experience building and testing ML models or building applied multivariate statistical models, particularly for data classification
Experience with self-supervised and semi-supervised learning.
Proficiency with Python and/or related analytical programming languages
Familiarity with Machine Learning and data processing related Python packages such as Scikit-learn, Pandas, Numpy, or Tensorflow.

Lightcast is proud to be an equal opportunity workplace and is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Lightcast has always been, and always will be, committed to diversity, equity, and inclusion. We seek dynamic professionals from all backgrounds to join our team, and we encourage our employees to bring their authentic, original, and best selves to work.

#LI-Remote


Data Scientist Insights Analytics

Virta Health is on a mission to transform diabetes care and reverse the type 2 diabetes epidemic. Current treatment approaches aren’t working—over half of US adults have either type 2 diabetes or prediabetes. Virta is changing this by helping people reverse type 2 diabetes through innovations in technology, personalized nutrition, and virtual care delivery reinvented from the ground up. We have raised over $350 million from top-tier investors, and partner with the largest health plans, employers, and government organizations to help their employees and members restore their health and live diabetes-free. Join us on our mission to reverse diabetes in 100M people by 2025.
As a full stack health care company of physicians, engineers, marketers and more under one roof, Virta collects comprehensive data on our patients’ experience, and leverages this data to build the next generation of health care for chronic diseases. Here at Virta, we rely heavily on Data and Analytics to optimize our product and workflow to improve our company’s KPIs as well as to demonstrate the value of the Virta Treatment to our customers.  We collect and organize disparate forms of patient data from both internal and external sources to generate insightful analyses.  We are looking for a senior data analyst/scientist with considerable experience working with healthcare data to help us collect, organize, and analyze this data, to generate insights and reports that we can use to further improve Virta’s performance.
Responsibilities

Execute I&A strategic plan to maximize Virta’s ability to leverage data to identify actionable insights to improve company performance
Generate reports (some in Looker) on KPIs, optimize and automate where possible
Participate proactively, in Squad level projects, including product, workflow redesign experimentation, advising ways to optimize the design through thoughtfully designed analyses
Operate in an agile fashion, prioritize allocation of limited resources to projects with the highest importance
Build pipelines that translate claims, clinical, and engagement data from our warehouse to inform experimentation and other analytic needs
Proactive identify and pragmatically solve challenges, including imperfections in data.
Lead cross-functional analytics meetings to keep stakeholders apprised of relevant KPIs and experiment outcomes
Support other I&A functions as the need arises

90 Day Plan
Within your first 90 days at Virta, we expect you will do the following:

Become familiar with I&A’s tools, the Virta product/workflow and how things work at Virta
Partner with product teams to design, implement, and analyze product experiments;  inform product roadmap by estimating KPI impact of future product initiatives
Provide analytics support for the Squad, including reporting, Looker dashboard and experimentation design
Provide analytics support to our various business units to answer questions about our business, patients, outcomes, etc.
Teach and inspire your team members through knowledge sharing, pair programming, and/or giving feedback during code reviews

Must-Haves

10+  years in a Healthcare Analytics, BI, Data Science or similar role
7+ years working with healthcare administrative data experience (claims, clinical outcomes, population health, etc.)
Have a bias for action with a natural orientation toward agile analyses

Able to influence senior decision makers. Some experience managing staff

Led projects from start to finish, working with multiple stakeholders, of diverse levels of analytic capabilities.

Comfortable working with imperfect data and dynamic environments with ambiguities and shifting priorities

Proficient in SQL and relational databases. Familiarity with data capture, ETL, validation, and test methods to standardize and automate analyses.

Familiarity with EHR, working knowledge of FHIR data structures
Experience using varied statistical methods using Python, R or similar
Some experience building BI dashboards, using tools like Looker, Tableau, Power BI
Ability to partner with the Data Infrastructure teams to inform infrastructure roadmap to best support your work
Experience working with cross-functional business partners to understand analytics or reporting needs

Nice-to-Haves

Advanced degree (M.PH/M.S./PhD) in Data Science, Stats, Actuarial science or similar
Expertise with EHR, working knowledge of FHIR data structures
Experience working at a technology company, bonus points for working at a “full-stack” company or marketplace where there is a complex relationship between different types of users
Proficient in Looker, Airflow, Jupyter, Pandas
Proficient in building BI dashboards
Experience calculating cost savings or economic impact of a value based program

Values-driven culture
Virta’s company values drive our culture, so you’ll do well if:

You put people first and take care of yourself, your peers, and our patients equally

You have a strong sense of ownership and take initiative while empowering others to do the same

You prioritize positive impact over busy work

You have no ego and understand that everyone has something to bring to the table regardless of experience

You appreciate transparency and promote trust and empowerment through open access of information

You are evidence-based and prioritize data and science over seniority or dogma

You take risks and rapidly iterate

As part of your duties at Virta, you may come in contact with sensitive patient information that is governed by HIPAA. Throughout your career at Virta, you will be expected to follow Virta's security and privacy procedures to ensure our patients' information remains strictly confidential. Security and privacy training will be provided.
For this role the compensation range for candidates in Colorado is $177,724 - $204,281; information about Virta’s benefits is on our careers page at: https://www.virtahealth.com/careers.


Data Scientist Europe

Who We Are:
Vista’s Data and Analytics (DnA) organization is working to make our company one of the world’s most well-known and successful data-driven companies. The cross-functional team includes product owners, analysts, technologists, data engineers and more – all focused on providing Vista with information and tools we can use to deliver jaw-dropping customer value. DnA team members are empowered to learn new skills, communicate openly and be active problem-solvers. Find out more at https://vista.io/
What You Will Do:
Collaborate with your Product Team to bring machine learning into transformative products for our customers
Engage with business partners to collaborate around analytical project requirements, define success metrics, explain methodologies and results, and negotiate work you're doing.
Build new models, segmentations, and algorithms; as well as analyze pre-existing data products, provide suggestions on how to evolve, and improve their efficiency.
Contribute to a roadmap making customer data products a core capability at Vista
Your Qualifications:
At Vista, we value the experiences that individual team members add to our culture. Please don't hesitate to apply even if you don't meet the exact qualifications, we look forward to learning more about you!
Degree in Computer Science, Math/Statistics or another technical field
1+ years of machine learning models development experience
Excellent programming skills in SQL and Python
Strength in clarifying and formalizing sophisticated problems
Nice to Have:
Daring Data Engineering chops to deliver end to end proofs of concept
Good knowledge of data visualization theory and tools (e.g. Tableau, Looker)
Relevant work experience in an agile eCommerce environment
Experience in Customer analytics domain
Why You'll Love Working Here:
Being at Vista means that you don’t see work as just a building, a desk or a manufacturing floor. You see it as a chance to take a step forward in your career journey – and your life. We strive to give you everything you need to learn, grow, and succeed. Through innovation, collaboration, and perpetual exposure to what’s next, we’re always pushing boundaries and broadening our horizons. We embrace the chance to operate outside of our comfort zone to discover what we’re capable of. Some might call that a challenge; we just call it another great day at work.
Vista has received numerous recognitions including a perfect score of 100 on the Human Rights Campaign Foundation’s 2021 Corporate Equality Index (CEI) naming us a Best Places to Work for LGBTQ Equality. We also earned a place as one of the best remote-first workplaces in the U.S. and on the Boston Best Places to Work list from Built In. In addition, Vista’s CEO, Robert Keane, was recently honored with Comparably’s Best CEOs award, listing him among the top CEOs according to employees.
Remote First-Culture:
In 2020, Vista adopted a Remote-First operating model and culture. We heard from our team members that having the freedom, autonomy and trust in each other to work from home and, the ability to operate when they are most productive, empowers everyone to be their best and most brilliant self. Vista also provides collaboration spaces for team members to work physically together when it's safe to do so or believe in-person working will deliver the best results. Currently we are enabled to hire remote team members in over 30 US States as well as many countries in Europe: including Spain, Germany, UK, Czech Republic, Ireland and Switzerland.
About Us:
As an e-commerce powerhouse, Vista is the design and marketing partner to millions of small businesses around the world. For over 20 years we’ve been inspired by small businesses, and we work incessantly to deliver solutions to their evolving needs. VistaCreate, 99designs by Vista and VistaPrint, all under the parent brand Vista, represent a full-service design, digital and print solution, elevating small businesses’ presence in physical and digital spaces and powering them to achieve success. Vista is focused on making great marketing and design accessible to every small business owner, allowing them to create a cohesive brand image for use in-store, online and on-the-go.
Equal Opportunity Employer:
Vista, a Cimpress company, is an Equal Employment Opportunity Employer. All qualified candidates will receive consideration for employment without regard to race, color, sex, national or ethnic origin, nationality, age, religion, citizenship, disability, medical condition, sexual orientation, gender identity, gender presentation, legal or preferred name, marital status, pregnancy, family structure, veteran status or any other basis protected by human rights laws or regulations. This list is not exhaustive and, in fact, in many cases, we strive to do more than the law requires.
#LI-SP1


Sr Director Data Science Apollo Team

Overview
11 West 19th Street (22008), United States of America, New York, New YorkSr. Director, Data Science - Apollo Team (Remote-Eligible)
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description:
Emerging Merchant Businesses is a new team dedicated to discovering and accelerating high-growth opportunities at Capital One.  Our newly formed organization is composed of incredibly exciting Capital One businesses, including Capital One Shopping, Flex Pay, and Apollo.  As part of the EMB team, you will  work alongside experts across customer experience, data, technology (and more!) who are moving quickly to find the next big business at the company.  We are looking for talented associates who are motivated to be part of this journey and help us shape the future of Capital One, growing and learning with a team who will invest in your development, foster an inclusive environment, and lead with heart to change banking for good.
As a Sr. Director, Data Scientist on the Apollo team in Emerging Merchant Businesses, you are a part of a team that develops the core technology which drives our industry-leading understanding of the U.S. business landscape, generating valuable business insight from many disparate sources. The Apollo team is building technology that allows us to acquire, understand, and make inferences on large, disparate business data sets. This requires ideas from across the machine learning skillset, applied to problems and data that are unique to our business.  You will do it all in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation.
In this role, you will:
Lead a cross-functional team of data scientists, machine learning engineers, data engineers, business analysts and product managers to deliver product(s) customers love.Lead machine learning and data science technical direction and execution (operations, governance, processes and practice) working closely with product management to craft a roadmap and success criterion.Lean on your strong background in graph-based machine learning, deep learning, software engineering and algorithm development to organize, grow and manage the ML/AI capabilities for the product.Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The ideal Candidate is:
Technical:Strong background in algorithmic and engineering practices in fields of machinelearning including entity resolution, graph-based ML or deep learning. You have hands-onexperience developing data science solutions using open-source tools and cloud computingplatforms.Innovative:Learns constantly, including developments in algorithms, libraries, frameworks andML technologies. You stay current on published state-of-the-art methods, technologies, andapplications and seek out opportunities to apply them.Customer first:You bridge the gap between business/product needs with ML design, engineering and execution. You identify the KPIs, resource needs, trade-offs and translate that into a ML roadmap.Creative: You thrive on bringing definition to big, undefined problems. You love askingquestions and pushing hard to find answers. You’re not afraid to share a new idea.A Strategic Thinker: You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You can set the team vision and make strong day-to-day decisions backed by that vision. Inspiring Leadership:You establish a culture of inclusiveness, cooperation and candor. You’re passionate about talent development, provide frequent actionable feedback to team members, and promote innovation.A Data Guru: “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyzedata from a variety of sources and structures. You know understanding the data is often the keyto great data science.Statistically-Minded:You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
A successful Candidate will have:
Experience setting and implementing broad strategic vision for ML applications, underlying platforms, and software Demonstrated technical expertise in building, testing, deploying and scaling of machine learning software. Experience with cloud, open source software packages, environment management, reproducibility, and governance.High motivation, adaptability and being collaborative. An individual who can handle ambiguity and enjoys building. Moving in a fast-paced environment excites you and are looking for an opportunity to be a member of an innovative team that will be building and implementing innovative products in banking.Excellent communication skills. You can present technical context in intuitive ways. You can read the audience and adapt your communication style to various stakeholders both internal and external to the Apollo organization.
Capital One is open to hiring a Remote Employee for this opportunity.
Basic Qualifications:
Bachelor’s Degree plus 9 years of experience in data analytics, or Master’s Degree plus 7 years of experience in data analytics, or PhD plus 4 years of experience in data analyticsAt least 4 years of experience in open source programming languages for large scale data analysisAt least 4 years of experience with machine learningAt least 4 years of experience with relational databases
Preferred Qualifications:
At least 1 year of experience creating and executing multi-year technical initiatives.At least 1 year of experience with containerization technologies and understanding on how to build for cloud scale delivery is a plusPhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analysis  At least 1 year of experience working with AWS.At least 3 year of experience managing people and leading cross-functional teamsAt least 4 years of experience with relational databases with strong SQL knowledgeAt least 5 years of experience with technologies such as python, sci-kit learn, PyTorch, Scala, or R for large scale data analysisAt least 5 years of experience with machine learningAt least 5 years experience in algorithmic and engineering practices in fields of machine learning including entity resolution, graph-based ML or deep learning
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
No agencies please.  Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace.  Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


Data Science Manager Anti Money Laundering

Overview
Center 2 (19050), United States of America, McLean, VirginiaData Science Manager, Anti-Money Laundering (Remote-Eligible)
Data Science Manager, Anti-Money Laundering
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
The Anti-Money Laundering Modeling and Advanced Data Insights team builds the machine learning models that identify potential money laundering, terrorist financing, or human trafficking. We develop data sourcing, predictive models, monitoring, and reporting using tools such as AWS, Snowflake, Python, Spark, and Rmarkdown. As the model developer for advancing transaction monitoring with machine learning, our team is responsible for end to end development, deployment, and monitoring of production models.
Role Description
In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers loveLeverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual dataBuild machine learning models through all phases of development, from design through training, evaluation, validation, and implementationFlex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Basic Qualifications:
Bachelor’s Degree plus 6 years of experience in data analytics, or Master’s Degree plus 4 years of experience in data analytics, or PhD plus 1 year of experience in data analyticsAt least 2 years’ experience in open source programming languages for large scale data analysisAt least 2 years’ experience with machine learningAt least 2 years’ experience with relational databases
Preferred Qualifications:
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analyticsAt least 1 year of experience working with AWSAt least 4 years’ experience in Python, Scala, or R for large scale data analysisAt least 4 years’ experience with machine learningAt least 4 years’ experience with SQL
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is open to hiring a Remote Employee for this opportunity.
No agencies please.  Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace.  Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


Senior Associate Data Scientist Anti Money Laundering

Overview
Locations: VA - McLean, United States of America, McLean, VirginiaSenior Associate Data Scientist, Anti-Money Laundering (Remote-Eligible)
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
The Customer Risk Rating (CRR) Next Generation Modeling team builds the machine learning models that identify potentially high risk customers. We develop data sourcing, predictive models, monitoring, and reporting using tools such as AWS, Snowflake, Python, Spark. As the model developer for the CRR program, our team is responsible for end to end development, deployment, and monitoring of production models.
Role Description
In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers loveLeverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual dataBuild machine learning models through all phases of development, from design through training, evaluation, validation, and implementationFlex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
Capital One is open to hiring a Remote Employee for this opportunity.
Basic Qualifications:
Bachelor’s Degree plus 2 years of experience in data analytics, or Master’s Degree, or PhDAt least 1 year of experience in open source programming languages for large scale data analysisAt least 1 year of experience with machine learningAt least 1 year of experience with relational databases
Preferred Qualifications:
Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)Experience working with AWSAt least 2 years’ experience in Python, Scala, or RAt least 2 years’ experience with machine learningAt least 2 years’ experience with SQLAt least 1 year of experience with Spark
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
No agencies please.  Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace.  Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


Data Science Associate

pulseData is changing the way healthcare data is utilized within major healthcare sectors. As a series A health-tech startup, we provide the insights necessary for medical staff to understand who has and is at risk of major chronic illnesses. We have rooted ourselves within the Kidney space, and have the capabilities of bringing our approach to many more patient populations given our capabilities.

We recently raised $16.5M in our series A and are growing fast. This means we are onboarding brilliant people and providing endless areas for our employees to grow their careers. We believe in trust and transparency, and enjoy a remote friendly working environment that promotes collaboration and diversity.

The Role:
In your role as a Data Science Associate, you will use machine learning to deliver insightful and actionable intelligence and predictive solutions to our team to improve Healthcare growth in our business. You will gain experience understanding healthcare and developing data driven solutions to improve care delivery, while working closely with other team members of our Data Science and engineering team to deliver value to our business partners. Aside from supporting our data science model creation and data teams, you'll also assist the product team with growth opportunities.

Qualifications:
Strong communication skills.
Cumulative GPA of 3.5 or higher.
Bachelor/Master Degree students pursuing degrees in data science, statistics, applied math, computer science, engineering or other quantitative fields providing sufficient data science foundations
Exposure to writing code (Python preferred, R and SQL okay), collaboration (Git), developing models (machine learning, boosting & bagging algorithms, &/or regression techniques), and performing predictive analytics testing and evaluation (match case analysis, ANOVA, confidence intervals, experimental design, A/B testing, etc.).
A hunger to learn and work on challenging problems.
Any prior experience working in a startup will be bonus points

Benefits/Perks:
A base between $60-$80k plus bonus
A remote working environment - you'll be working eastern (ET) hours.
Top tier benefits including medical, dental, and vision insurance - 85% of which is covered by pulseData.
Unlimited PTO - so you can stay at your best year round!
Fun gym discounts, a 401k, and a new laptop + equipment.
Company offsite adventures throughout the US each year.
Tons of room for growth and the ability to learn new things.

This role NOW offers sponsorship.

Chronic Kidney Disease (CKD) is a substantially under-diagnosed condition that affects 37 million people in the US. Today, clinical and care management teams use our platform to identify the most at risk-individuals and proactively deliver care in advance of adverse events, delivering better clinical outcomes at a lower cost. Our clients are risk-bearing healthcare enterprises: ACOs, kidney clinics and nephrology practices, large health systems, managed care and health insurance companies. Together, we use data science to deliver more human care.

pulseData is backed by some of the best investors in the industry, recently raising a $16.5M Series A led by Bain Capital and Two Bear Capital.


Data Scientist Healthcare

About ClosedLoop:
ClosedLoop.ai is healthcare’s data science platform. Purpose-built and dedicated to healthcare, we make it easy for healthcare organizations (HCOs) to use AI to improve outcomes and reduce costs. Our platform combines an intuitive end-to-end machine learning platform with a comprehensive library of healthcare-specific features and model templates.
We’re the leader in delivering unbiased accuracy and explainable AI healthcare solutions. Regardless of whether our customers have extensive data science teams or are just starting out, our products are engineered to help them harness the power of AI to improve patient outcomes, achieve clinical excellence, and enhance business success.
What sets us apart is our commitment and ability to deliver AI solutions at-scale in healthcare. We’re ready to help change the world. Are you? Come join us!
About the Role:
ClosedLoop is looking for a customer-facing Data Scientist to build and deploy predictive models for our healthcare customers. ClosedLoop data scientists utilize our platform and work alongside our customer’s data science teams to deliver machine learning models into real world healthcare settings. In addition to ensuring the quality of the models, you will also help customers understand how to integrate those models into their processes and to measure the effectiveness of the models in production.
What you'll do:

Building predictive models on healthcare data using the ClosedLoop platform.
Work with customer teams to ensure that models are deployed and integrated into real world decisions.
Cleaning and vetting of a wide variety of healthcare data (claims, medical records, labs, ADT, etc) using the ClosedLoop platform.
Train and educate customer data scientists on best practices for data science in healthcare.
Create presentations and present model results to both technical and non-technical audiences
Make suggestions and provide commentary to the product management and engineering teams on how to improve the platform.

What you'll bring:

Bachelors or higher in Computer Science or related experience
5+ years of engineering experience with Python
Prior experience with healthcare data science required
Understanding of machine learning and statistical analysis

Why ClosedLoop:

Competitive salary
Equity
401K plan
100% company covered for medical, dental, and vision for employees and their families
Flexible PTO

Employee Testimonials:

"Exciting place to work! - Company has a great vision for the role of machine learning (and AI) in healthcare. Exciting to go to work every morning!"
"Work Hard and Feel Rewarded - The CEO and CTO have total faith in their team, and the employees ideas and opinions are highly respected and listened to. The passion for our company's mission is contagious from the executive team, which makes our high standards fair and rewarding."
"Room to thrive"
"Passionate People, Supportive Environment, & Strong Vision"


Healthcare Data Science Consultant

About ClosedLoop:
ClosedLoop.ai is healthcare’s data science platform. Purpose-built and dedicated to healthcare, we make it easy for healthcare organizations (HCOs) to use AI to improve outcomes and reduce costs. Our platform combines an intuitive end-to-end machine learning platform with a comprehensive library of healthcare-specific features and model templates.
We’re the leader in delivering unbiased accuracy and explainable AI healthcare solutions. Regardless of whether our customers have extensive data science teams or are just starting out, our products are engineered to help them harness the power of AI to improve patient outcomes, achieve clinical excellence, and enhance business success.
What sets us apart is our commitment and ability to deliver AI solutions at-scale in healthcare. We’re ready to help change the world. Are you? Come join us!
About the Role:
ClosedLoop is looking for a customer-facing Healthcare Data Science Consultant (known internally as a Data Scientist) to build and deploy predictive models for our healthcare customers. ClosedLoop data scientists utilize our platform and work alongside our customer’s data science teams to deliver machine learning models into real world healthcare settings. In addition to ensuring the quality of the models, you will also help customers understand how to integrate those models into their processes and to measure the effectiveness of the models in production.
What you'll do:

Building predictive models on healthcare data using the ClosedLoop platform.
Work with customer teams to ensure that models are deployed and integrated into real world decisions.
Cleaning and vetting of a wide variety of healthcare data (claims, medical records, labs, ADT, etc) using the ClosedLoop platform.
Train and educate customer data scientists on best practices for data science in healthcare.
Create presentations and present model results to both technical and non-technical audiences
Make suggestions and provide commentary to the product management and engineering teams on how to improve the platform.

What you'll bring:

Bachelors or higher in Computer Science or related experience
5+ years of engineering experience with Python
Prior experience with healthcare data science required
Prior experience in a professional services/consulting position required
Understanding of machine learning and statistical analysis

Why ClosedLoop:

Competitive salary
Equity
401K plan
100% company covered for medical, dental, and vision for employees and their families
Flexible PTO

Employee Testimonials:

"Exciting place to work! - Company has a great vision for the role of machine learning (and AI) in healthcare. Exciting to go to work every morning!"
"Work Hard and Feel Rewarded - The CEO and CTO have total faith in their team, and the employees ideas and opinions are highly respected and listened to. The passion for our company's mission is contagious from the executive team, which makes our high standards fair and rewarding."
"Room to thrive"
"Passionate People, Supportive Environment, & Strong Vision"


Data Science Specialist

EBANX is a global fintech founded in 2012 with a mission to be the leading payments partner in rising markets. With its own technology and infrastructure, combined with in-depth knowledge of the Latin American market, EBANX allows these companies to connect to hundreds of payment methods in different countries in the region. And it goes further, creating results for businesses and simple shopping experiences for consumers.
From the beginning of our journey, we have an important mission: to give access. And this is not just about our products and services, but it goes through everything we are and do. We believe that it is only possible to innovate with diversity, so we cherish differences in gender, race, nationality, disability, sexual orientation, religion and age. Plurality is what makes our Big Dream possible.
We are called ebankers and we are changing the way people buy, connect, and live globally. Let's make history together?
As a Data Scientist Specialist your mission will be to build and deploy machine learning models to serve multiple business units of the company.
You will also be responsible for:

Build and maintain machine learning models that are relevant to the payments industry (e.g. real-time transactional model, anomaly detection, routing optimization and churn prediction).
Work closely with devs and core business areas (fraud prevention, finance, commercial, products and marketing) to define business problems and create solutions leveraging our data.
Be able to propose new projects, gain stakeholder buy-in, calculate business value, be a cooperative team player and develop strong relationships with colleagues.
Explain and solve complex problems in straightforward terms.
Work directly with the data engineering team to create data pipelines and transformations necessary to be consumed by models.
Ad-hoc exploratory analysis and experiments.
Promote the use of data as the main driver for decision making.

Main requirements for this position:

Should be proficient at writing complex codes with languages like: Python, Pyspark and SQL.
Relevant work experience working with core compute and storage cloud services (preferably AWS).
Previous experience designing and building supervised ML models using Random Forests, Boosting, SVM or deep learning (some experience with at least one of the main libraries/frameworks like XGBoost, Sklearn and Tensorflow).
Understand the trade off and implementation differences between batch vs streaming.
Work with transactional DBs and analytical tools like Redshift, BigQuery and Athena.
Good knowledge of development tools like git, bash and containers.

What else would we like to see?

Experience in design solutions based on AWS services and tools (Lambda, Kinesis Data Stream, Kinesis Data Firehose, S3, Dynamo, OpenSearch, EMR, Sagemaker, ElastiCache), carefully read the docs, implement the entire architecture you designed with the support of your peers, and document it.
Some experience with visualization tools (e.g. Tableau, Qlik or Looker).
Previous experience working in a startup environment.

EBANX offers:

A challenging environment, with opportunities to grow;
Casual office and flexible dress code;
Spanish, English and Portuguese classes;
WAVES - Program of goals and results (variable compensation);
EBANX Play - Wellness (Gympass, e-Sports, SESC );
Semi flexible hours (8 hours a day - Monday to Friday);
Meal Allowance;
Transportation voucher (if needed);
EBANX Education: scholarship;
EBANX Skills: budget for workshops and courses;
EBANX Flexible: monthly Day Off from February to November, birthday Day Off and Rest up Month - one month of paid leave every three years of work anniversary.
EBANX Family: Daycare assistance, extended leave for caregivers and support program for children and pregnant women;
EBANX Health: Health and Dental Insurance, with subsidy for dependents, and medicine subsidy for ebankers;
Life Insurance: Life Insurance 100% paid by EBANX
Hello ebanker: psychology, finance and legal orientation.
Blue Club: Exclusive discount for ebankers in bakeries, restaurants, courses, electronics store and more!

Follow us on LinkedIn and check out our Instagram to learn more about the #ebanxlife.


Data Scientist Revenue Senior Staff

#TeamNextdoor
Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on.
Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 295,000 neighborhoods across 11 countries.
Meet Your Future Neighbors
As a Data Scientist at Nextdoor, you will be responsible for design and oversight of product experiments, own complex analysis to drive company and product strategy, and deploy online and offline models to a production environment. We use a semi-embedded team structure, in which a group of data team members works on a specific product or pillar, interfacing directly with product and engineering stakeholders. The Data Science group is made up of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as psychology, geology, physics, and statistics. We are the mathematical decision scientists for their product development organization and play an active and collaborative role in building and improving the product.
The Impact You’ll Make
At Nextdoor, Data Scientists have the opportunity to work across a wide range of problem areas, including member and small business onboarding, growth, feed ranking, community vitality, monetization, and experimentation. As a Data Scientist on our Revenue team, you’ll focus on driving value for businesses of all sizes - from multinational brands to your local coffee shop. The work is essential to the growth and success of the company and involves frequent opportunities to deploy code as well as showcase progress to teammates, stakeholders, and company leadership.
What You’ll Bring To The Team

Advanced degree in a quantitative field and 4+ years working in data science, product analytics, or machine learning, or equivalent
Excellent knowledge of Python or R, including common scientific computing packages and data science tools such as numpy, pandas, and scikit-learn
Expertise with methods, tools, and packages for statistical modeling and machine learning
Experience formulating, running, and sharing complex analyses, including different types of experiments, causal inference studies, and other exploratory analysis work
Experience architecting, debugging, and executing complex SQL queries
Intermediate knowledge of at least one big data technology such as Hive, Presto, or Spark
Excellent written and oral communication, including ability to effectively communicate complexity to a diverse group of stakeholders
Curiosity about how things work, from both a business and technical perspective
A collaborative spirit and a commitment to community
It’s ok if you don’t have all of these requirements; if you think you’d be a good fit for the role, please get in touch with us!

Bonus Points

Work experience related to social or community-based products
Work experience related to small businesses and marketplaces
Work experience related to advertising and auction systems
Expertise deploying models to production
Expertise in testing and evaluating the impact of network effects
Knowledge of web applications and service-oriented architecture

At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.
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Data Scientist Marketing

#TeamNextdoor
Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on.
Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 295,000 neighborhoods across 11 countries.
Meet Your Future Neighbors
At Nextdoor, our Growth Marketing team is charged with driving member growth and revenues from businesses advertising on the platform. This team has a Marketing Science function which utilizes the analytical horsepower of data science focused purely on new customer growth on the platform. We are looking for a data scientist to grow the team and increase our ability to support the optimization of growth marketing decisions.
Think of the role as a full-stack marketing data science, using data to inform and guide marketing decisions.  You will be responsible for the design and execution of best practices with regards to experimentation for email campaigns including selection, measurement and reporting of results to influence next steps. Engage in discovery work to identify opportunities to change the what/when/how of our current programs.
The role requires a strong mix of technical and statistical skills with the ability to collaborate cross-functionally with stakeholders including but not limited to finance, data science, marketing. Familiarity with campaign management and marketing will be helpful.
The Impact You’ll Make
You will have an opportunity to work in a growth focused organization and make a huge impact by optimizing how we communicate to a high volume of people. Your work will come to life through strategic/analytical thinking, operational excellence and creatively solving complex business problems. We will want you to want to own analytical projects end-to-end, taking an ambiguous problem and forming a structured opinion. Defining success metrics that capture performance and identify actionable insights
Your responsibilities will include:

Developing actionable segmentation
Best-practise experimentation to give us reliable insight
Establish a shared vision with cross functional teams to develop/optimize/deploy new strategies including MarTech, marketing managers and wider data science teams
Campaign management
Identify where we can invest in 3rd party data to enrich our decision making capabilities
Build out required performance measurement tools and dashboards
Educate stakeholders by explaining the “Why” behind the “What”

 What You’ll Bring To The Team

2+ years of expertise in quantitative analysis, ability to tell a story backed by data using data mining methods

2+ years of experience using in-depth applied statistics and analytical experience in partnership with Marketing teams to optimize decision making

Demonstrating proactivity in identifying better ways of working and can recommend actionable solutions
Ability to pull together your own datasets with strong SQL skills and knowledge of analytical programming languages including R or Python to conduct statistical analysis
Familiarity with experiment design and A/B test analysis including measurement selection
Can communicate effectively with a range of stakeholders
Curiosity for discovery and creativity in solving complex challenges

Bonus Points

Experience building predictive models using machine learning algorithms
Familiarity with marketing in the B2B space
Experience with complex attribution solutions
Worked with data vendors to enrich data
Knowledge of online advertising and ad tech space; robust understanding of online advertising best practices

At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.
#LI-Remote


Staff Data Scientist Sustainability

About Indigo

Indigo Ag is a mission-driven company dedicated to harnessing nature to help farmers sustainably feed the planet. We innovate across a breadth of technology and science disciplines to help enhance agriculture's long-term sustainability and profitability and mitigate the climate crisis. We seek to positively impact the world through the digital and biological solutions we bring to the market, creating a more resilient earth, healthier economies, and thriving communities. Our people build partnerships, explore the science, and engineer the technology to help grow the future of sustainable agriculture. The only way to achieve it is through a unique combination of expertise – from Fortune 500 to academia, soil science and agriculture, to tech start-ups.

About the team:

The Sustainability Data Science team is a multidisciplinary team that harnesses data science, statistics, and technology to build a data-driven, scientifically-rigorous sustainability program. Our activities span several aspects including: operational tasks to conservatively quantify Carbon sequestration approaches, rates, and efficacy partner with our science team on more R&D activities to design, analyze, and derive actionable insights from the frontiers of sustainability and carbon-sequestration field experiments and sensor technologies strategic decision support with forecasting and scenario planning partner with the product team on tools, processes, and data products to enhance the grower’s Carbon and Source program experience.

About the role

We are looking for a staff-level data scientist to lead growth and engagement activities within the Sustainability Data Science team. The success of the Carbon program will hinge, in part, on top-of-funnel success. To expand the program and maximize our impact to the business and to the environment will require finding not just growers but the right growers. That is, those who are interested in regenerative practices but who face barriers that prevent them from adopting those practices. Who and where are the growers we can help transition to regenerative practices? What do they have in common? Where can we find more? How can we find and reach them? For those that we acquire, what is their lifetime value (LTV) and churn risk? How do we keep them engaged and successful?The data will span transactional data, web analytics, as well as a rich set of open and proprietary agronomic and demographic datasets. As such, analyses may span questions around growth, engagement, and agronomics insights at a variety of spatial scales. This role will encompass typical growth and engagement data science activities such as churn prediction, LTV, lookalike modeling, lead scoring, segmentation, session analysis, and experiments partnering with a range of stakeholders across commercial, marketing, product, tech, data, and data science. It will also involve building personalized data products collaborating with product, tech, and other data scientists on the team.

Competencies
Proven ability to independently translate needs into Data Science problems by asking the right questions and delivering solutions by identifying necessary data, building models, and producing actionable results.5+ years practical industry experience in supervised and unsupervised machine learning including, regression, classification, time series forecasting, feature selection, evaluation, model selectionStrong expertise in data wrangling / munging (we work mostly with Python and SQL)Excellent communication, consulting, and story-telling skills,and able to work well with a range of stakeholders with varying backgrounds and levels of technical expertise.Mentor more junior members and contribute to the overall culture, standards, and processes of the team.Strong sense of quality and attention to detailCurious and proactive. Bias for action.

What will you do?
Lead, coach, and mentor junior data scientistsReview machine learning models and codeWork with our product managers and business stakeholders to identify and scope the highest value data science problemsExplore and understand our data and how they can feed production-grade machine learning modelsProactively utilize data and business understanding for feature engineeringBuild, prototype, and deploy state-of-the-art machine learning models to solve real business problemsCommunicate, interpret, and explain modeling output to stakeholdersMeasure value of the machine learning models we deploy

Preferred Qualification:
Masters Degree or PhD in Computer Science, Math, Statistics, Physics, Engineering, or related quantitative fieldExperience in a startup environmentExperience working with geospatial data is a plus, as is experience building growth engagement models.

#LI-Remote

At Indigo, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and team members. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, sex, pregnancy (including childbirth, lactation, and related medical conditions), national, social or ethnic origin, age, physical, mental or sensory disability, marital status, family or parental status, sexual orientation, gender identity and/or expression, family medical history or genetic information, military and veteran status, and any other characteristic protected by applicable law. Indigo believes that diversity, equity, and inclusion among our team members are critical to our success. We seek to recruit, develop and retain the most talented people from a diverse candidate pool.

If you’re applying for a job in the U.S. and need reasonable accommodation for any part of the employment process, please email talent@indigoag.com and let us know the nature of your request and contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address.


Principal Data Science Dhl

About This Role
Discover. A brighter future.
With us, you’ll do meaningful work from Day 1. Our collaborative culture is built on three core behaviors: We Play to Win, We Get Better Every Day & We Succeed Together. And we mean it — we want you to grow and make a difference at one of the world's leading digital banking and payments companies. We value what makes you unique so that you have an opportunity to shine.
Come build your future, while being the reason millions of people find a brighter financial future with Discover.
Job Description
At Discover, be part of a culture where diversity, teamwork and collaboration reign. Join a company that is just as employee-focused as it is on its customers and is consistently awarded for both. We’re all about people, and our employees are why Discover is a great place to work. Be the reason we help millions of consumers build a brighter financial future and achieve yours along the way with a rewarding career.
Responsible for working closely with management to execute analytical initiatives. Responsible for providing thought leadership & strategic thinking to solve business problems by leveraging techniques such as segmentation, optimization, advanced analytics and machine learning. This position will closely monitor performance metrics and KPIs to ensure goals are met and course correct as necessary.
Responsibilities
Provides thought leadership & strategic thinking to translate business problem into analytical framework(s), and independently recommend actions and provide business insights. Operates as a subject matter expert on statistical analysis, test and design of experiment, analysis methodology, modeling & application, and financial impact analysis. Collaborates with cross-functional partners to understand their business needs, formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations. Facilitate implementation of work product and ensure accuracy. Establishes and maintains effective performance tracking; identifies improvement opportunity, form hypothesis, propose, design and implement tests to drive strategy enhancement and optimization. Leads the development and implementation of advanced analytics including customer segmentation, optimization, prescriptive analytics and machine learning algorithm & recommendation to solve business problems. Lead the development of Analytical capabilities with the aim of creating long-term strategic data/analytics assets for the company.
Delivers effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information. Develops and automates reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs. Consistently follows standard work processes and documentation requirements. Recommends improvement to work processes to increase efficiency while maintaining quality of work. Continuously improves technical and leadership skills through training and development.
Minimum Qualifications
At a minimum, here’s what we need from you:
Bachelor’s Degree in Analytics, Engineering, Statistics or related field 6+ years of experience in Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling/Data Science or related field
Preferred Qualifications
If we had our say, we’d also look for:
Master’s Degree in Analytics, Engineering, Mathematics, Statistics or related field 4+ years of experience in Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling/Data Science or related field
What are you waiting for? Apply today!
And by the way, while you're waiting to hear from us, don't forget to check out the great benefits Discover offers.
The same way we treat our employees is how we treat all applicants – with respect. Discover Financial Services is an equal opportunity employer (EEO is the law). We thrive on diversity & inclusion. You will be treated fairly throughout our recruiting process and without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other characteristic protected by federal, state, or local law in consideration for a career at Discover.
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#LI-KS1
What are you waiting for? Apply today!
All Discover employees place our customers at the very the center of our work. To deliver on our promises to our customers, each of us contribute every day to a culture that values compliance and risk management.
The same way we treat our employees is how we treat all applicants – with respect. Discover Financial Services is an equal opportunity employer (EEO is the law). We thrive on diversity & inclusion. You will be treated fairly throughout our recruiting process and without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status in consideration for a career at Discover.