nathansutton/data-science-job-descriptions huggingface dataset:
Data Scientist Summer at Sprinklr

What You’ll Do:
Sprinklr is seeking a Data Engineer to join the Modern Analytics team and partner together on data architectures that support enterprise reporting and analytics. This person will work closely with colleagues to develop data flows in Snowflake and in Tableau, providing solutions that yield important insights to the company.
In this role, you should have a background in ETL, data engineering and BI Reporting. Additionally, you should be analytical and an excellent communicator, and also have a business acumen, problem-solving and “can do” aptitude.
Additional responsibilities are as follows:

Contribute toward the design, deployment, and maintenance of data flows in Snowflake; support key datasets that yield structured and timely access to actionable business insights
Ensure that the architecture and data pipelines are aligned with best practices and reporting standards, all the while upholding security, performance, robustness and reliability
Build new and exciting reports and dashboards in Tableau, all the while working with colleagues to interpret insights from the data.
Act as a teammate on a small team, where on any given day, you may wear different hats, roll up your sleeves, and do what is needed to get the job done
Develop a deep understanding of data sources and know exactly how, when, and which data to use to solve particular business problems
As part of development efforts, ensure that technical documentation is created and maintained, along with the capture of business requirements and acceptance criteria that pertain to the technical solution
Contribute to the continual improvement of the business’s data platforms through observations and well-researched knowledge.
Keep a pulse on industry best practices and trends, offering opportunities for process and system improvements
Monitor the existing metrics, analyze data, and lead partnership with other Data and Analytics teams in an effort to identify and implement system and process improvements.

Qualifications:

Degree in Computer Science, Information Systems, or related field.
Experience in SQL and Python; Snowflake and Tableau experience is a plu
Proficiency with data manipulation and analysis, along with the ability to build, maintain and deploy sequences of automated processes.
Demonstrated ability to write clear code that is well-documented and stored in a version control system
Excellent listening, interpersonal, communication and problem-solving skills
Data Scientist Intern Summer at Sprinklr

What You’ll Do:

Engage in exploratory data analysis in alignment with business and technical requirements. The data may span across Sales, Finance, HR, Customer and Operational domains.
Build base models to support business needs and iterate on those models to tune parameters.
Develop and deploy predictive models based on historical data that provide future predictions for specified enterprise objectives.
Build and maintain reporting dashboards in Tableau in order to provide insights to stakeholders.
Offer methodology recommendations to consider for advanced analysis projects (predictive models, clustering / segmentation, etc).
Where needed, engineer data to support enterprise data needs and provide the basis from which data science algorithms can be applied.
Coordinate with different functional teams to build and implement models and monitor outcomes.
Design, build and manage automation tools using Python/ Apps Script/ VBA for a wide range of business requirements.
Identify the key organizational trends using statistical modeling and machine learning, and propose action plans working closely with stakeholders
Use analytical rigor and statistical methods to analyze large amounts of data, extracting actionable insights using advanced statistical techniques such as data analysis, data mining, optimization tools, and machine learning techniques and statistics (e. g., predictive models, LTV, propensity models).

 
Who You Are & What Makes You Qualified:

Masters in a field that emphasizes analyzing, displaying, or reporting on data (e.g., data science, computer science, statistics, math, engineering).
Thorough coursework and/or work experience in the field of Data Science, possess experience in building and productionizing machine learning / AI algorithms for classification, regression, clustering, time series forecasting, topic modeling, anomaly detection etc.
Experience with tools such as Python, R, Tableau, SQL and any other related programs for implementing the above responsibilities.
Good understanding of data visualization principles and fundamentals of probability and statistics.
Advanced presentation skills to share key insights with executives, senior leadership and business stakeholders
Experience with data management and having an understanding of data structures as well as data ingestion, blending, transformation and visualization techniques.
Senior Data Scientist Workforce Analytics Americas at Atlassian

Atlassian can hire people in any country where we have a legal entity, assuming candidates have eligible working rights and a sufficient timezone overlap with their team. As our offices re-open, Atlassians can choose to work remotely or return to an office, unless it’s necessary for the role to be performed in the office. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. 
Are you an analytics champion with a deep toolset who thrives on helping business partners strategize, implement and measure data-driven initiatives? Do you relish the opportunity to dive headfirst into vast, high-impact projects and make foundational contributions across analytics, strategy and operations? If so, this role is for you!
As a Senior Data Scientist, Workforce Analytics on our Customer Support Services (CSS) team, you will partner closely with key business leads, focus on some of the most exciting challenges Atlassian faces.
Some examples of what you will be doing:
Work closely with finance, product, and CSS leadership teamBe responsible for predictive modeling and analyses of workforce data: workforce growth, organization structure, and talent managementOwn and drive improvement of inbound business volume forecasting; working with Operations partners to better enable staffing, training, and optimization of resourcesOwn and enhance predictive pipelines and advanced analytic tools support CSS Workforce Management forecasting and allocationKey contributor to workforce planning strategy which is critical to Atlassian customer support experienceWork closely with Data Engineering team on measurement and data instrumentation maturity
Some examples of the skills and tools you'll use are:
Analytics: Statistics, predictive modeling, advanced analytics, metrics and measurement, ETL automation, and data pipelines, data story tellingTools: SQL, Tableau, R / Python, Excel, etc.Collaboration: Confluence, Jira
Senior Forecasting Decision Scientist Americas at Atlassian

Atlassian can hire people in any country where we have a legal entity, assuming candidates have eligible working rights and a sufficient timezone overlap with their team. As our offices re-open, Atlassians can choose to work remotely or return to an office, unless it’s necessary for the role to be performed in the office. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. 
We are looking for a top-tier data scientist to join our Decision Sciences team as a Senior Forecasting Decision Scientist. As a member of the decision science team, you’ll be providing the models and insights that empower teams across our business to learn quickly and make smart investments. Atlassian is experiencing rapid growth, so there are plentiful chances to create an impact in this role.
You are passionate about bringing structure to complex business problems. Your models will create powerful feedback loops between incoming data and decision-makers. Working alongside data engineers, data scientists, and product leaders, you’ll be monitoring business performance and translating insight into improved business forecasts. You've got demonstrable experience with building and deploying predictive models and a proven track record of fostering strong and trusted relationships with stakeholders, with whom you turn data into action.
On your first day, we expect you to have:
5+ years of relevant experience using data to build software at industry-leading companiesExpertise in SQL and one of Python or R3+ years of applying statistical and econometric methods that uncover actionable insights, estimate causal relationships or derive predictions.Demonstrable experience in deploying production-grade predictive models in close collaboration with engineering teams, product leaders and business stakeholders.Excellent communication to garner trust and bring forecasts close to product driversAbility to turn complex findings and results into a compelling narrative and a set of actionsStrong sense of accountability, self-drive, and the ability to function independentlyPassionate about products, and about analytics as a craftUndergraduate in a technical subject from a top school
It’s great, but not required, if you have:
Exposure to advanced statistical or econometric techniques (e.g. survival analysis, vector autoregression, general linear models, Markov models and panel data methods)Experience in both enterprise (or B2B) as well as consumer (or B2C) environmentsTrack record of presenting at meet-ups and conferencesMS, MBA or PhD degree in a relevant topic
Principal Data Scientist Confluence Performance Americas at Atlassian

Atlassian can hire people in any country where we have a legal entity, assuming candidates have eligible working rights and a sufficient timezone overlap with their team. As our offices re-open, Atlassians can choose to work remotely or return to an office, unless it’s necessary for the role to be performed in the office. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. 
Confluence is changing the way companies collaborate and share information. More than half of Fortune 100 companies, hundreds of thousands of teams, and millions of users use Confluence every day to get their jobs done, faster and more collaboratively. Join us as we unleash the power of teams all over the globe.
We are looking for a top-tier data scientist to work on Confluence product analytics. The role needs to manage a multi area within product analytics, with the possibility of having direct reports.
Product performance and scalability is the backbone of any B2B cloud products. On top of this, user’s needs for workplace collaboration products are fast evolving.  Therefore, this role is multidisciplinary.  You need to have the skills to dig deep into both performance and API data as well as usage data,  connect the dots together quickly and communicate insights in a way that persuades action. Your product managers, UX designers, and full stack software engineers, lean on you for data informed decisions. Particularly for this role, you will have the opportunity to shape product roadmap.
On the first day, we'll expect you to have:
5+ years of experience in a product analytics functionExpertise in SQL and proficiency in PythonThorough understanding of usage data creation process and experience of partnering with engineering teams for data trackingExperience in designing and analyzing product experimentsAbility to turn complex findings into a compelling narrative and a set of actionsTrack record of influencing decision-making using analyticsBackground in Engineering or quantitative subject (e.g. Mathematics, Physics, etc)
It's great, but not required if you have:
Experience in both enterprise (or B2B) as well as consumer (or B2C) environmentsManagement experience
Data Scientist Varying Levels at Windfall Data

Founded in 2016, Windfall Data is on a mission to determine the net worth of everyone on the planet. The company helps nonprofit and for-profit organizations to more effectively identify, understand, and engage affluent consumers with the industry’s most reliable and accurate dataset available. More than 750 organizations use Windfall Data to identify and engage their most promising constituents. As a company, we are growing quickly, and every member of our team has a tangible impact on the success of our business and our customers.

At Windfall Data, data is our product — and data science lies at the heart of everything we do. We are looking for experienced data scientists who are able to run machine learning models in production from day one, and who are driven to deeply understand and build upon our unique data assets. 


Responsibilities

Build production-quality, custom predictive models to enhance and expand our core product
Investigate new data sources, perform statistical analyses, and document findings
Work with engineering and data vendors to improve the accuracy of our data sources  



Requirements

Advanced degree in a quantitative discipline
5 – 12+ years of full-time data science experience, including applied techniques in modern data science and machine learning in production environments
Expert knowledge of Python & SQL
Collaborative, team-focused attitude with a strong desire to advance the product and learn new things
The ability to communicate technical ideas to a non-technical audience
Self-starter with experience turning ideas into actionable designsExcellent written and verbal communication
Eligible to work within the United States



Perks

Small team = opportunity for a big impact 
Compensation includes equity and a competitive salary
Excellent company-sponsored benefits
HQ at great location in downtown SF (Jackson Square), option for remote work within US
Director Of Data Science at Outdoorsy

Outdoorsy is looking for a Director of Data Science to join our Engineering team. If you’re passionate about the outdoors and would like to work in a fast-paced environment, then we want you! Fun fact: Outdoorsy has been recognized on the Forbes list of America’s Best Startup Employers in both 2020 and 2021.Job SummaryA hands-on data leader who enjoys both data engineering and science. You're a stickler for proper data infrastructure and you're not afraid to voice your opinion if something isn't designed properly. A/B testing design should be second nature as we lean tech-forward into production-ready ML implementations for automated risk analysis, search ranking and dual-sided marketplace pricing. We’ve got a passionate data team already with room to grow.Qualifications Strong communication and interpersonal skills. Must have an interest in working in a highly collaborative environment Experience designing and implementing a/b tests following statistical principles Must be a "doer" with a "roll up your sleeves" attitude 5+ years of architecting data and business intelligence platforms/ data warehouse 3+ years of experience building, designing, and managing production machine learning models with a focus on optimization Experience presenting data and using data visualization tools such as Tableau  Experience transforming vague problems into algorithmic solutions Strong manager of people and projects across reporting lines Excellent influencing skills and a proven collaborator Highly organized with outstanding project management and execution skills Ability to juggle multiple priorities and make things happen in a fast-paced, dynamic environment; strong bias for action Benefits & Perks Opportunity to help build a company from an early stage Competitive salary Equity in one of the world's fastest growing companies Comprehensive health and welfare benefits 401(k) Match Flexible PTO 2 paid RV rentals per year-- we believe in balance and taking the time to nourish mind, body, and soul.  About usOutdoorsy is the most trusted RV rental and outdoor experiences marketplace on the planet. We have grown from a lofty white-board idea in 2015 to over $1B in total transactions. Outdoorsy’s mission is making memorable outdoor experiences accessible to everyone. We are creating jobs and helping individuals, couples, and families realize financially life-changing freedom. With offices worldwide in the US, Canada, Australia, Europe and the UK, we’re mobilizing the 56+ million idle RVs and campervans around the world to ensure everyone has the access, choice, and opportunity to safely spend more time outside.We're passionate about our customers, collaborative consumption, community, and entrepreneurship. We’ve been motivated by our values from day one: we always put the customer ahead of ourselves. We like winning. We make long-term progress in the world and repay our gratitude in every community interaction.Outdoorsy has been recognized on the Forbes list of America’s Best Startup Employers in both 2020 and 2021.
Principal Data Scientist at Citizens Bank

Description
This Principal Data Scientist will be responsible for developing analytical insights and/or statistical models that optimize business and marketing spend, identify new business/marketing opportunities and/or provide strategic direction to senior management.
This position will collaborate directly with business partners to play a key role in the development and application of models, insights and data intelligence that supports business and marketing programs, customer analytics and operational improvements.
Primary responsibilities include:
Researching growing market trends and mine the Citizens data intelligence to develop new insights that can guide the strategic direction of the Citizens Bank lines of businessAnalyzing current business processes and programs and developing models/strategies/insights that can lead to a more optimal business performance and spend of marketing dollars.Documenting and communicating technical/analytic results for a non-technical audience
Location is not a barrier for this role and while our preference would be to have a chosen candidate with onsite capabilities in one of our corporate headquarters – we are open to remote employment within the United States for an experienced candidate.
Qualifications
Required Skills/Experience:
5 - 10 years of experience in Analytics/Database Marketing, with experience in Financial Services preferred5 - 10 years of experience in SAS and/or related programming languagesStrong written and verbal communication skills required with an ability to successfully communicate analytic results, business insights and resulting business implications to non-technical business partnersAbility to work in a team environment and collaborate with colleagues who have a background in statistics, database development/maintenance, and information technology Strong programming skills and ability to utilize a variety of data/analytic software languages/tools (e.g., SQL, SAS, R, Python, Splus, etc.)Deep knowledge of a variety of statistical concepts and procedures, including generalized linear models, machine learning algorithms, experimental design, stochastic processes, markov process modeling, response surface methodology, and statistical graphics
Education, Certifications and/or Other Professional Credentials:
Master's Degree in Statistics/Mathematics/Applied Math required, PhD preferred
This position is not available in Colorado. 
#LI-Sourcer1
Staff Data Scientist Revenue Cycle at Invitae

By joining Invitae, you’ll work alongside some of the world’s experts in genetics and healthcare at the forefront of genetic medicine. We’ve crafted a culture that empowers our teams and our teammates to have the biggest impact and to explore their interests and capabilities. We prize freedom with accountability and offer significant flexibility, along with excellent benefits and competitive compensation in a fast-growing organization!
Invitae is seeking a Staff Data Scientist to join the team and lead efforts to improve the company's reimbursement performance. Reporting to the VP of FP&A and Business Analytics, the Staff Data Scientist will work closely with leaders in the billing and reimbursement, technology, finance, commercial, and customer experience teams. Over time, this position may expand in scope to include other areas of high strategic importance to the company.
Responsibilities:

Develop a structured understanding of opportunities to improve the company's revenue cycle performance from insurance companies through analysis of claims and other data.
Evaluate the impact of initiatives under consideration and monitor performance after implementation.
Support analysis with statistical or machine learning models as needed to further our understanding of root causes.
Design and develop dashboards, models, and presentations to communicate insights and recommendations to leadership.
Think strategically about the company's broader business objectives; put proposed initiatives and set analytic priorities in that context.

Requirements:

Bachelor's or Master's degree in a related field such as Data Science, Business Analytics, Statistics, Biostatistics, Computer Science, or a relevant quantitative field preferred.
8+ years of relevant experience in data analysis, preferably in the healthcare industry. Experience with healthcare claims data preferred.
Typically requires a minimum of 12 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or a PhD with 5 years experience. Any equivalent combination of training, education, and experience that provides the required skills, knowledge and abilities.
Familiarity with healthcare reimbursement policies and procedures a plus.
Strong proficiency in SQL and Excel. Proficiency in Python for data analysis, model development, and visualization.
Experience with statistical and/or machine learning model development.
Demonstrated ability to work independently, prioritize effectively, and think strategically in a fast-paced environment.
Excellent communication skills, with the ability to communicate complex ideas to leaders at the VP level and above.
Highly analytical thinker with excellent problem-solving skills.

Remote in US
#LI-Remote
Senior Data Scientist Machine Learning at Rec Room

Rec Room is the best place to build and play games together. Players can chat, hang out, play in millions of rooms, or build something new to share with the world! We have a vibrant commercial ecosystem within Rec Room, and our goal is to enable creators to be rewarded for their work. Come join us on the ground floor to help optimize the ecosystem for both players and the business.  
As a Senior Machine Learning Data Scientist, you’ll be responsible for designing, developing, and implementing machine learning models to power our in-game store recommendations and serve users content that they’d find valuable. You’ll be supporting creators in making a living on the platform, as well as playing a critical role in the success of Rec Room as a business. 
WHAT YOU'LL DO:

Design, develop and implement production-facing ML models to deliver valuable commerce content to our users.
Collaborate closely with the ML Infra team to define a roadmap that powers real-time personalized ranking models.
Design and run A/B tests, analyze model performance, and deep dive into the data to uncover opportunities for improvements.
Build out pipelines in collaboration with our Analytics Engineering team to enable model building on top of sophisticated features.
Set best practices, mentor, and provide guidance to the more junior Data Scientists.

WE ARE LOOKING FOR INDIVIDUALS WITH: 

Master's or Ph.D. degree in computer science, statistics, mathematics, or a related field
5+ years of ML ranking experience in a production setting
Strong proficiency in programming languages such as Python, R, and SQL
Deep familiarity with ML infrastructure to collaborate with our infra team
Extensive experience with experimentation.
dbt knowledge is a plus
Spark/Databricks knowledge is a plus

COMPANY INFO TO KNOW: 
The base pay range for this position is $138,750-231,250 per year; however, the base pay may vary depending on job-related knowledge, location, skills, and experience. Stock options and, in some cases, a sign-on bonus may be offered as part of the compensation package. We also offer a full slate of benefits, including flexible vacation, medical, dental vision, life and disability coverage, long-term care insurance, FSA, commuter benefits, a 401(k) plan with company match, and a parental leave program. We also offer some not-so-standard benefits, including equipment, family, and pet care stipends.
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.
Lead Data Scientist Operations Research And Simulation at Rivian

Rivian is seeking a simulation expert to assist in designing and optimizing fulfillment process using discrete event simulations for Commercial Operations. Perform process modeling and simulations, statistical analysis, and design on experiments to drive decisions on processes and designs.
Responsibilities

Build Discrete Event Simulation (DES) models to build, simulate, and optimize the fulfillment operational process flow models using FlexSim, Demo 3D, AnyLogic or any other Discrete Event Simulation (DES) software packages to determine future state performance under varying conditions
Understand process flows, analyze data, perform Design of Experiments, and effectively represent in simulation model to achieve better correlation and process improvements
Analyze, interpret and facilitate process improvement initiatives among site operations, logistics, last mile operations and upper funnel groups.
Enhance models on ongoing basis to ensure continued alignment with business.
Examine key business data by identifying, cleaning, and providing analysis and insights. Validating data fidelity and creating data where none currently exists.
Generate insights and present findings to senior management using data visualization and presentation programs to make business recommendations.
Key partners to collaborate with include IT, Finance & Accounting, Treasury, Manufacturing & Engineering, Various Operations Teams, People Team, Strategy, Marketing, Commercial Analytics

Requirements

Master’s degree in Operations Research/Industrial Engineering, Statistics, Mathematics or related technical field required
3+ years of experience in building simulation models – discrete event simulation, agent based and hybrid simulation models.
Proficiency in Python, Java or other programming languages
Proficient in SQL, Tableau, and Excel.
Familiarity with AWS preferred
Experience in supply chain
Ability to quickly understand and map systems, processes, and operations
Experience in a dynamic and agile environment requiring high-adaptability, management of multiple projects, excellent cross-functional communication and presentation skills
Continuous improvement attitude: ability to suggest and implement best practices
Willing to travel (up to 5%)

Salary Range for New York City (not state) Based Applicants: [ 162,000 - 210,000 ] (actual compensation will be determined based on experience, location, and other factors permitted by law).
Quantitative Analyst at Clipboard Health

About the Role
Quants at Clipboard Health develop, deploy, and monitor mathematical algorithms to clear per-diem transactions across labor markets. They are independent thinkers who can innovate rapidly in a domain with virtually no pre-existing literature.
This is a high ownership role, where contributors own pricing problems all on their own. They're expected to find clues, design solutions, run experiments, and deploy successful strategies to the entire marketplace at an extremely fast pace (every 1-2 weeks). Quants also talk to customers, write a lot to keep the organization updated on their thinking, and participate in weekly meetings where they report on the progress of their initiatives (in writing).
What is the Pricing Team?
The Pricing Team is a new team at Clipboard Health that builds real-time, automated systems to price (and reprice) each shift in the marketplace to reflect the evolving dynamic between labor supply and demand. 
Qualifications
Our interview process is focused on two case studies. They are the cornerstone of how we evaluate candidates. The qualifications below are only meant to serve as a helpful benchmark. 

B.A., M.A., or PhD in a quantitative discipline, or equivalent quantitative experience.
Experience programming, ideally with Python. JavaScript experience is helpful.
Ability to write complex SQL queries.
Deep understanding of probability theory.
1+ years of experience in a high-growth environment is preferred but not required. New graduates are welcome.

Benefits

Competitive compensation, in line with quant roles at financial firms
Equity in a high-growth startup
Meeting-light, remote culture
Unlimited vacation
Data Scientist Healthcare at Closedloop

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 senior, 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
Prior experience working in a customer facing consulting position 
Understanding of machine learning and statistical analysis

Why ClosedLoop:

Competitive salary
Equity
401K
100% company-paid health insurance for medical, dental, and vision for employees and their families
Flexible PTO
Remote work

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"
Senior Data Scientist at Moz

Description
The Moz Group Data Engineering teams are looking for an experienced Data Scientist with a strong Python background. This position will work from an engineering perspective with both the engineering and product teams to improve data modeling within our services and products. The ideal candidate will have experience using a broad set of statistical and machine learning techniques including supervised / unsupervised data sets and NLP.
Responsibilities
Comfortable learning Moz's SEO domain, creating appropriate models, and working with engineering and product teams to see those models implemented and released in the context of a standard framework, e.g. Spark or HadoopComfortable engaging with both engineering and product teams to educate them on data science topics, identify opportunities to apply data science to further our business and operational objectives, and advocate for action based on these identified opportunities 
Technologies
Python Cloud providers, e.g. AWSPrototyping, e.g. Jupyter NotebookFrameworks, e.g. Spark, Hadoop, pandas
Data Science Skills
ForecastingInferential statisticsRegression / classificationNLP, e.g. Word2Vec
About the Moz Group
The Moz Group, a subsidiary of Ziff Davis, Inc (NASDAQ: ZD), is a leading provider of marketing technology solutions primarily for small and medium-sized enterprises that empowers businesses to engage their customers digitally and grow their revenue by leveraging the power of online search, email, voice, and text communications.
About Ziff Davis
At Ziff Davis, we work in a culture of collaboration and welcome those who desire to join our growing global community. We seek enthusiastic individuals with an entrepreneurial spirit looking for and environment that rewards your best work.
Ziff Davis offers competitive salaries, health benefits, and company-sponsored events. If you are seeking a dynamic work environment where you can see the direct impact of your performance, then Ziff Davis is the place for you. We offer a fun and friendly working environment where individuals are given the opportunity to learn, grown and build on their skills.#Moz
Director Ai Products at Hubspot

HubSpot is the #2 best company to work for on Glassdoor. We’re also scaling in every dimension: users, revenue, people, technology, systems, and more.
We’re looking for a Director of Product to develop and lead the vision and strategy of AI/ML at HubSpot. You will report directly to the GM & VP of Product and build/grow teams of Product Managers and Product Leaders to support the AI strategy.
This is a great opportunity to lead a relatively new, yet highly visible and strategic Product Group at HubSpot. The group already has a talented team of PMs, a strong foundation of AI practices & infrastructure, and a highly successful flagship product (Conversation Intelligence). We need a seasoned Product leader to help expand our AI/ML platform, to greatly increase our portfolio of AI Products, and scale our team of AI PMs. This person will be looked upon to be the vision and voice of AI/ML across HubSpot.
What you’ll do
Establish the vision & strategy for AI/ML across HubSpot’s CRM platform
Build, coach and empower a diverse team of PMs to support the AI/ML strategy
Drive adoption of our flagship AI-based product - Conversation Intelligence
Identify opportunities and launch new flagship AI-based products
Enable other product teams across HubSpot to leverage our AI/ML platform & infrastructure to leverage/integrate AI throughout their products
Represent HubSpot as a thought leader and visionary in AI
Create and foster an inclusive culture
What we are looking for
7+ years experience building and developing medium-to-large teams of high-performing Product Managers and Product Leaders
Deep domain expertise in AI & Machine Learning
Experience building and growing successful, user-facing AI-based products
Experience identifying and launching new products (0→1) and scaling existing products
Experience working with C-level stakeholders, Product, and Engineering leadership to establish and sell a product vision and strategy
Superb written and verbal communication
Data-driven orientation and growth mindset
An obsession for understanding and improving user experience
Ability to build trust, respect, and empathy, and to foster a sense of team and mission
Someone who can add to the culture of the product team and cares about diversity, inclusion and belonging
Lead Data Science Analyst at Discover

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
Responsibilities
Leads the development and implementation of advanced analytics including customer segmentation, optimization, prescriptive analytics and machine learning algorithm & recommendation to solve business problems. 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. Delivers effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.  Establishes and maintains effective performance tracking; identify improvement opportunity, form hypothesis, proposes, designs and implements tests to drive strategy enhancement and optimization. Manages multiple priorities, communicate business performance and project progress to management & business partners. Develops and automates reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs. Facilitates implementation of work product and ensure accuracy. 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, or Statistics 4+ years of experience in Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling/Data Science or related. 
Preferred Qualifications
If we had our say, we’d also look for:
Master's Degree in Analytics, Engineering, Mathematics or Statistics 2+ years of experience in Credit Risk, Fraud Risk, Marketing Analytics, Optimization, Operations Analytics, Modeling/Data Science or related 
What are you waiting for? Apply today!
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.
Senior Data Scientist at Mission Lane

Mission Lane’s Data Science Team is looking for a Senior Data Scientist to join us.
You’ll be a successful Senior Data Scientist if:

You’re personally motivated to help improve the financial health of the 100 million working-class Americans who live paycheck-to-paycheck
You’ve created, deployed, and managed supervised learning models in production systems for vital applications
You enjoy being a technical mentor. You share best practices for software engineering and can help smart, educated, people with hard mathematical problems.
You consider yourself a generalist data scientist and are more motivated by practical solutions than theoretical elegance
You practice solid fundamentals with software engineering (test-driven development, code review, refactoring) and the PyData stack (numpy, scikit-learn, pandas, etc.)
You can communicate, collaborate, compromise, and be sensitive to the needs of clients and your teammates

 
We are offering:

A low-ego, respectful, data science team committed to solving practical problems together
The chance to work at a company where data science is at the heart of the business and integral to both our day-to-day operation and our executive team’s strategic vision
Flexible work hours and flexible work location (even after the pandemic)
A generous parental leave policy
Excellent opportunities for career growth, with both management and technical tracks for advancement
A team that values learning and approaches work with a “growth mindset”
A competitive salary, equity, and a full benefits package (health, dental, vision, 401k)

 
You might be particularly excited about the role if you want:

To work on fairness, accountability, and transparency in machine learning (FAccT ML) or explainable AI (XAI)
To find practical ways to apply modern innovations from diverse research areas like Causal Inference, Cost-Sensitive Machine Learning, and Time Series Classification
To use distributed computing systems like Spark and Snowflake to manipulate data

If you’re excited about the role and aren’t sure if you meet all the requirements - we want you to apply anyway! We believe people can contribute to our team in a wide variety of ways and want to meet people who find meaning in our mission and our technical work compelling.
 
Job Location: Remote or Richmond, Virginia
Data Scientist at The Home Depot

OverviewQualificationsJob DescriptionBenefits

Bonus Eligible

401(k) Company Matching

Employee Stock Purchase Program
Data Scientist Supply Chain Rpa at The Home Depot

OverviewQualificationsJob DescriptionBenefits

Bonus Eligible

401(k) Company Matching

Employee Stock Purchase Program
Sr Actuarial Analyst at Root

The Role.
Root's approach to data and technology has opened the door to new ways of auto pricing: new data everywhere, new analytical approaches, and the massive computational power to finally put the two together. We're looking for actuaries that are ready to roll up their sleeves and get their hands dirty, building better processes and analytics from the ground up.
We're looking for a Senior Actuarial Analyst to execute and enhance our rate revision process and pricing analyses by developing and communicating key insights to drive effective decisions.  There's no playbook on how to do this; you'll be partnering within and between teams to creatively problem solve and incorporate insights into a final product.
What you'll be doing.
Execute pricing initiatives including state implementations and rate changes for auto and renters products
Support rate filings and engineering implementations
Leverage statistical and projection models to develop rating plans and recommendations for pricing improvements (example: rate indications, limit studies, state specific analysis etc)
Evaluate and analyze market data to facilitate competitive strategic decisions
Opportunities for growth with company into management or other more senior roles
What we're looking for.
3+ years of P&C insurance experience in an actuarial role
Demonstrable experience with analysis in R, Python or other programming language
Demonstrable experience in SQL or other database software
Actuarial Analyst at Root

Root's approach to data and technology has opened the door to new ways of auto pricing: new data everywhere, new analytical approaches, and the massive computational power to finally put the two together. We're looking for actuaries that are ready to roll up their sleeves and get their hands dirty, building better processes and analytics from the ground up.
The position.
We're looking for aActuarial Analyst to execute and enhance our rate revision process and pricing analyses by developing and communicating key insights to drive effective decisions.  There's no playbook on how to do this; you'll be partnering within and between teams to creatively problem solve and incorporate insights into a final product.
What you'll be doing.
Execute pricing initiatives including state implementations and rate changes for auto and renters products
Support rate filings and engineering implementations
Leverage statistical and projection models to develop rating plans and recommendations for pricing improvements (example: rate indications, limit studies, state specific analysis etc)
Evaluate and analyze market data to facilitate competitive strategic decisions
Opportunities for growth with company into management or other more senior roles
What you should have.
1+ years of P&C insurance experience in an actuarial role
Demonstrable experience with analysis in R, Python or other programming language
Demonstrable experience in SQL or other database software
Data Scientist Machine Learning Ads Targeting at Reddit

Location: Remote-Friendly 
Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly and will continue to be after the pandemic. 
We are looking for a Machine Learning Data Scientist to work within the Ads Targeting team. You will work closely with engineers and product managers to 1) develop algorithms and toolings to empower various ML focused Targeting products, 2) shape the product roadmap and strategy.
Responsibilities:

Build machine learning models to improve ML focussed Ads Targeting products such as User Lookalike Models, Keyword Targeting, User Interest Matching.
You will design metrics and mechanisms to understand and evaluate the performance of various Targeting products. 
Be involved in all phases of modeling such as ideation, offline modeling, online implementation, experimentation, deploy and post-launch monitoring/measurements.
Serve as a thought-partner for product managers, engineering managers in shaping the Targeting roadmap and strategy by identifying opportunities through deep-dive analyses and/or modeling.
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. 

Required Qualifications:

Experience in machine learning applications of natural language processing, recommendation system, large scale unsupervised learning.
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
Strong analytical and communication skills
Strong skills in SQL and programming (Python or R) 
Understanding of experimentation and causal inference analyses
Experience in online advertising is preferred but not required

Benefits:

Annual Personal & Professional development funds
401k matching plan
Flexible PTO
Paid holidays + Wellness days 
Remote friendly