nathansutton/data-science-job-descriptions huggingface dataset:
Engineering Manager Data Science And Machine Learning at Bolt

The Financial Products team owns two of the most important areas with respect to a retailer’s online operations: payments and risk. Bolt strives to work with all credit card payment processors and Alternate Payment Methods (APMs) offering our end customers the greatest variety of choice in determining how they want to pay. For our retailers, our risk product gives them confidence we are approving the most amount of orders while keeping the fraudulent chargeback rate down.
 
The Risk team specifically identifies and stops fraudsters, enabling merchants to rest assured when accepting online payments.
Check out our Engineering Blog! 
Responsibilities: 

Manage an 8-10 person cross-functional engineering team
Own roadmaps, prioritization, technical architecture and day to day technical oversight for their team
Own the hiring plan, collaborate with recruiting on executing on it, assess and close candidates
Coaching engineers on your team to help them grow personally and professionally
Build relationships with stakeholders across the organization to index for greatest impact

Requirements:

BA/BS in a technical field. Computer Science or Computer Engineering is a plus
1+ years as a manager of engineering team(s)
6+ years experience as an individual contributor on an engineering team
Prior experience managing engineers at Venture backed or large scale tech firm
Experience working with teams split across several sites is a plus
Data Scientist at Bolt

The Data Platform team works closely with all teams and cross-functional partners (including product, engineering, and data analysts) to build a foundational data stack powering business analytics.
We are looking for someone to play a mission-critical role in designing and building the data mining algorithms, and data analytics pipelines at Bolt. We’re looking for someone with the experience, creativity, and passion for producing world-class technology who can support our product, leadership and marketing teams with insights gained from analyzing our data. Other teams at Bolt, other companies, and consumers alike will rely heavily on what you build, and you’ll have a ton of trust and responsibility. If challenges excite you, and you’re ready for a large one, let us know.
Check out our Engineering Blog!
Responsibilities

Build production ready data mining and big data analytics algorithms and pipelines; your models will be the engine that powers all online commerce through Bolt
Conduct data analysis to determine which policies we adopt and help inform strategic growth
Build statistical models, data pipelines, data mining, data analytics, and production ready services to serve offline and live traffic
Work with other teams at Bolt to engineer data models and extract data insights that help improve Bolt business

About you

Passion to improve e-commerce businesses
Strong communication skills in a cross-functional team
Unrelenting focus on impact
Ability to formulate business problems into quantitative objectives and developing methodological solutions

Requirements

MS/PhD in math, statistics, computer science, or other quantitative field
3+ years of experience in developing ML/statistical models in an applied setting
Knowledge of statistical concepts and techniques such as statistical inference, causal inference, or predictive modeling
Knowledge of data mining, and big data analytics techniques
Experience with big data processing pipelines and orchestration tools
Mastery in SQL or other big data processing languages
Experience with one of the programming languages such as Python, R, Java, Scala

Preferred

Experience with big data technologies such as BigQuery, Spark, Dataflow, Apache Beam, Pubsub, Cloud Functions, EMR, S3, Glue, Kinesis Firehose, Lambda
Data Scientist Europe at Leadfeeder

Leadfeeder is a fast-growing international SaaS scale-up, headquartered in Helsinki, Finland. We are an international remote team of 130+ members from around the world. We've developed an online service which automates sales lead generation for B2B companies.
Our 50+ strong in-house, all-remote engineering team is responsible for developing new features, and otherwise improving and maintaining the Leadfeeder product.
We are organised in feature-oriented, cross-functional squads. Each squad is responsible for specific features of the product, and works tightly together with high autonomy.
We pride ourselves on keeping apps working smoothly, and the codebase tidy and well-tested. We dedicate time for upgrades, refactoring, and overall improvements for developer productivity and happiness.

As a Data Scientist, you will be joining the R&D to own everything related to product analytics there. Your main focus will be analytical support for the Data Quality Tribe, which is responsible for traffic identification, the core functionality of Leadfeeder.
You must reside in Europe, yet the exact location doesn’t matter as Leadfeeder is a remote company.

Responsibilities
As a Data Scientist concentrated on Data Quality analytics, your tasks would include (but no limited to) the following:
Implement machine learning techniques into Leadfeeder’s core technology offering Communicate design of data and machine learning solutions to your teammates 
Work alongside the Tribe members to develop mission-critical KPI's Create dashboards and reports for key areas of the Data Quality Partner with engineering to create and assess product experiments Help growing a culture of measurement and metrics Investigate the causes behind unexpected metric fluctuations Develop models to automatically detect anomalies
Requirements
Excellent SQL skills Good understanding of statistics behind A/B testing and regression analysis Experience with BI/Visualization tools like Tableau, Qlik or similar Basic understanding of APIs Some programming skills (Ruby, Python etc.) Good understanding of machine learning techniques Strong English language skills, both written and spoken
Benefits
The chance to work with a very knowledgeable, high-achieving and fun team An international and diverse work atmosphere The opportunity to work remotely in a fast-paced and results-oriented startup environment Personal budget for home office improvements Company hardware or monthly financial support for using your own equipment Flexible working hours Access to weekly yoga / fitness / meditation classes online Mental Health support Bi-annual company retreats
Apply for this position 
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Analytics Research Manager Heor at Happify Health

About the Role
At Happify Health, the Health Economics & Outcomes Research (HEOR) team is critical to developing and communicating evidence to support economic value propositions to payers, employers and healthcare systems. The Research Analytics Manager will be supporting HEOR evidence generation needs for Digital Therapeutics and Care Delivery solutions. We are looking for a versatile candidate who has strong tactical execution skills that can implement HEOR data analytics strategy. If you are passionate about enabling access to mental health care through generating evidence by designing and implementing innovative HEOR analytical studies, Happify is the place for you. This job reports to the Director of HEOR. 
#LI-Remote
Responsibilities

Responsible for conducting statistical analysis to explore economic impact of Happify solutions on real-world health utilization (disease incidence, treatment patterns, costing, etc.) combining various data sources (i.e. claims data, clinical trial data, real-world user data)
Generate evidence related to quantifying the economic burden for chronic disease states of interest analyzing administrative healthcare data, such as Medicare or commercial claims data.
Prepares research results and written summaries to internal teams or clients, and for journal publications.
Supports initiatives to improve efficiency/standardization across all projects.. 
Evaluates complex statistical/programming issues, and oversees implementation of rigorous data quality assurance plans; collaborates and/or communicates with internal teams to resolve issues.
Plans statistical programming activities / timelines to provide project team with guidance on data management and analysis timelines for projects

Qualifications

3-5+ years’ experience in designing and implementing statistical analysis to support health services and claims database research (3+ years with a PHD) within the medical device/ Pharma industry (may include time in relevant consulting agencies)
Flexible and collaborative mindset with the ability to work in a dynamic environment
Strong tactical skills in executing HEOR analytics studies
Excellent written and verbal communication skills, with demonstrated success in publishing abstracts and/or manuscripts.
Versatile team member who enjoys frequent collaboration and who can also take initiative to work independently; genuinely invested in Happify’s mission and success
Proficiency in Statistical Analysis System such as SAS or R required
Master's degree or higher in Statistics or Biostatistics or other relevant field with substantial statistical preparation is preferred; strong knowledge of statistical methodology and analysis is required
Data Science Lead at Moonpay

The team  ❤️ 
The data team is here to build, maintain and serve the best in class data platform to the whole of MoonPay, enabling all the teams to be able to take key data driven decisions and gain further insights into our operations. We're well established within MoonPay but there is still more than ample opportunity for you to come in with your own ideas and help shape our future.
Tech Stack 💻
GCP, BigQuery, Postgres, Python, Airflow, DBT, Looker
 
What you’ll do 👀 

Lead the data science team by identifying and leaning into opportunities to advance the data science discipline at MoonPay.
Mentor and manage a small team of data scientists of various levels (from associate to senior).
Establish and scale the design of MoonPay’s data science platform. 
Decide on what priorities require the most attention; help set goals and metrics in order to influence product and operational decisions.
Work closely with business partners and articulate their data science needs.
Work cross functionally with other teams to streamline processes towards successful deliverables. 
Work closely with talent and recruiting teams to grow and scale up the team.
Collaborate with the rest of the data team to improve our overall data ecosystem and enforce best practices across the team and department. 

You should apply if you have the following ✅ 

5+ years of experience in a data science role within a fast-paced, agile and highly variable environment, preferably within the technology sector.
1+ years in a lead position, either as a technical or people lead.
Advanced SQL knowledge.
Advanced knowledge and experience in an object-oriented language, ideally Python, but others are considered.
Deep and broad understanding of statistics, especially as applied to experimentation and testing
Deep and broad understanding of model building, deployment and maintenance.
Be able to apply machine learning principles and techniques within the context of various business needs. 
Demonstrated ability to convey clear narratives about complex data models and concepts to audiences with varying levels of technical knowledge.
Keen eye for operational and technical excellence.
Lead Data Scientist at Paper

Paper is looking for a Lead Data Scientist to join the growing R&D and Data Science team. In this role, you will be responsible for managing technical aspects of data science projects to ensure the success of delivered solutions. You will spend a significant amount of time designing, planning, and executing technical solutions. You will work closely with our applied research scientists and engineers across the organization. You must be self-directed and comfortable providing guidance on applied research projects in Analytics and Machine Learning domains. You are eager to collaborate with a wide range of stakeholders and functional teams. The ideal candidate will have a strong background in mathematics/statistics/computer science or a related field.
This position can be located in any geography in the US or Canada.
Responsibilities:

Identify strategic technical objectives and lead data science technical roadmaps from ideation to implementation.
Improve the technical quality of the codebase via developing quality standards, leading training sessions, and enforcing code review processes.
Work with stakeholders throughout the organization to identify roadblocks and execute to unblock technical hurdles.
Mentor and coach data scientists on the team by providing direct feedback or comments in code reviews as well as leading pair sessions.
Lead rituals such as planning and retrospective meetings and backlog grooming to ensure consistent velocity.
Manage the team’s workload by controlling technical debt.
Collaborate with different functional teams and communicate technical and non-technical decisions.

Qualifications:

5-7 years of experience in data analytics and building statistical models, with a Master’s or PhD in Statistics, Mathematics, Computer Science or another quantitative field.
+2 years of experience leading highly technical and analytical teams.
Proficiency in Python and Data science libraries including Numpy, SciPy, Pandas, Scikit-Learn, Tensorflow, Pytorch, MatplotLib and Seaborn (R and Matlab is a plus).
Experience manipulating data and drawing insights from large data sets.
Solid knowledge of production infrastructure and pipelines for Data science solutions.
Knowledge of a variety of machine learning techniques (supervised and unsupervised, clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Experience working with and creating data architectures.
Knowledge of GCP cloud services.
Experience visualizing/presenting data for business stakeholders.
Strong problem solving skills with an emphasis on product development.
A drive to learn and master new technologies and techniques.
Excellent written and verbal communication skills for coordinating across teams.

Job perks:

Work with a dynamic team that provides support whenever you get stuck.
100% remote work.
Bi-annual company wide meetups.
Opportunity for career development with a fast-growing company.
A unique opportunity to make an impact by making education more equitable.

#LI-remote #LI-HD01
Senior Data Scientist at Healthsherpa

About us
We help people find, enroll in, and use ACA (a.k.a. Obamacare) health coverage. We've helped over 9 million people enroll, saving over $30 billion through government subsidies in the process. We've doubled enrollments and revenue each year for the past 3 years, and we are now the largest ACA enrollment platform afterHealthCare.gov. We're profitable and on track to make mid-eight figure revenue for 2021.
We're a mission-driven team that advocates for and cares about the people we serve. We are a double bottom-line company - revenues and enrollments in ACA coverage. The ACA brings high-quality, comprehensive, and affordable health coverage within reach for low-income Americans. And we exist to make that promise a reality. Your contribution will positively affect millions of people, helping them to navigate the complex and confusing health insurance industry and to access health care when they need it.
We are committed to building a team balanced in representation to best serve the people who use our products. We believe in creating inclusive and equitable spaces, which build trust and respect and foster a sense of belonging. These values are at the core of our culture, and we genuinely believe they will continue to lead our organization to successful outcomes.
About the role
We are looking for a Data Scientist to join our team to use our unique data set to improve the product, increase revenue, and set strategy. You will have substantial autonomy in determining how you achieve these goals, and you will also set our data science roadmap. You will report directly to the CTO and your work will contribute directly to increasing the number of people that can access healthcare affordably.
You Will:
Analyze data to identify product improvements and revenue opportunitiesEstablish product and business health metricsDesign, deploy and analyze experimentsBuild machine learning models for multiple applicationsWork with engineers to improve data infrastructure
You Have:
Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering, or relevant work experience5 or more years of industry experience in a data science or analytics roleProficiency in SQLProficiency in Python, R or another data science and visualization environment
What we offer
Great compensation package that includes meaningful equity in a high growth, profitable companyHealth, vision and dental coverage for you, your spouse and dependents401K after grace periodEmployee assistance programParental leavePaid Vacation and holidaysMonthly grocery stipendHome office budget for remote team membersOffices in San Francisco and Sacramento with catered lunch for working on-siteCommuter benefit
We're building a diverse and inclusive work environment where we learn from each other. We welcome and encourage people of diverse backgrounds, experiences, identities, abilities and perspectives to apply. We are an equal opportunity employer and a fun place to work. Come join the team at HealthSherpa.
Data Scientist at Antenna

We're looking for an inquisitive and analytical Data Scientist to join our highly skilled team. You will have the opportunity to advance our most important initiatives because of your detailed diligence in writing and managing models, designing new models, and proactively collaborating with the Product team. 
You will report to our Director of Data Science. Antenna is remote-empathetic and welcomes applicants from anywhere in the United States.
What You’ll Do

Make our data the most accurate in the business – assess the viability of new data sources, experiment with different approaches, and combine methods to ensure this happens.
Develop and maintain custom data models and algorithms to apply to data sets, including predictive modeling and demographic projections.
Build out our coverage universe so that we can provide accurate information on every subscription business within our purview.
Support research and development in large scale data mining and information retrieval in online media consumption behavior.

Who You Are

You love data – and enjoy pushing the boundaries and having a keen eye for what insights can be gleaned from it 
You have 3-5 years of work experience in validating, processing, and analyzing data 
You have hands-on experience with exploratory data analysis, statistical data analysis such as linear models, multivariate analysis, time series analysis, as well as machine learning techniques
You have a proven track record of turning state-of-art research into production-ready products
Proficient coding skills (SQL/Python/R) and database knowledge
Experience working with a cloud based platform to ingest, transform, schedule and deploy data models
You can explain how models and systems work to both non-technical and technical stakeholders
Demonstrated ability to work independently with partners in other parts of the company
Passionate about process improvement and diligent when creating measurement solutions
Bonus: Have an understanding of applied statistics and market research (qualitative, quantitative, behavioral, experimental) research methodologies
Bonus: Can flourish in dynamic and often-changing environments; results-driven with an ability to effectively multi-task
Data Scientist at Limeade

About us:  
Limeade is an employee experience software company that helps build great places to work. Our platform unifies employee well-being, engagement, and inclusion solutions with industry-leading communications capabilities. Recognized for its own award-winning culture, Limeade helps every employee know their company cares. To learn more, visit www.limeade.com.
We're committed to creating a mission-driven, positive and inclusive culture of improvement made up of the best and brightest people in the business. And we've got the awards to back it up: Puget Sound Business Journal ranked us #1 Best Workplace in Washington, and Seattle Business ranked us one of the top three Best Companies to Work for in Washington State. In addition, we're one of the fastest-growing companies in North America (Deloitte's Technology Fast 500™), and Fortune magazine recognized us as a Best Workplace for Women. Limeade is a global company that embraces a distributed workforce and has users in more than 100 countries. Our headquarters are in Bellevue, WA.
About the role:
Limeade is seeking a Data Scientist I for a small but mighty Personalization team. In this role, you contribute to taking Limeade through its ML-first future, where best-in-industry algorithms are deployed throughout the platform to personalize the experience for all their users.
Responsibilities:  
Building and implementing Machine Learning models utilizing Databricks in the Azure cloud
Researching and implementing MLOps best practices to enhance the Personalization team’s machine learning lifecycle process
Performing statistical analysis to validate models
Communicating findings and recommendations to the business
Requirements:
Ability to demonstrate our values in an on-going and consistent way
Bachelor’s degree in relevant field & min. 2 years exp.; or advanced degree w/out exp.; or equivalent work exp.
Strong programming skills in Python and SQL
Excellent understanding of machine learning techniques
Experience with big data platforms
Knowledge of statistics and experiment design (e.g. A/B testing, causal inference)
Ability to communicate complex technical work to a non-technical audience
Limeade provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, Limeade will provide reasonable accommodations for qualified individuals with disabilities.
Please Note: Limeade is currently unable to support visa sponsorship for those living in the United States and working under an H1B visa.
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Sr. User Experience Researcher
Senior Data Scientist at Cars Com

About the Role
Data Science is the driver for our future at CARS. The team aims to build explainable algorithmic systems that help us solve business problems, create new opportunities and democratize intelligence for everyone while ensuring data ethics as the highest priority.
We are looking for a data scientist who has a passion for applying statistical methods in solving business problems. This individual will work with Data Scientists/Engineers, Product Managers & Designers, Analytics and Industry researchers, and will be responsible for building creative solutions that the auto-industry is facing today and the ones that aren't even discovered yet. 
As we look to engage consumers in their car-shopping journey, we aspire to learn consumer behavior and its effect on the auto industry in general. To that end, the candidate will build econometric and machine learning models for causal inference and prediction and apply economic theory to solve business problems.
An ideal candidate should have business acumen, technical skills in quant and programming, and should be able to communicate effectively to a diverse audience. 
What will you do?

Develop state-of-the-art methodologies for research problems that have high business impact, including areas of statistical and causal inference, econometrics, etc.
Work to help shape how CARS approaches issues related to pricing, measurement of Ad effectiveness and incrementality etc. 
Collaborate with market research, communications and product teams on data visualization methods and use it to explain trends in auto industry
Design ML models to predict user behaviors and implement experiments to measure their impact on key product outcomes
Experience in deploying models to production and/or experimentation
Mentor fellow data scientists and folks across the company, who needs mentorship in leadership and technical skills 

Basic Qualifications:

Advanced degree in Economics, Statistics or related field
Expertise with at least one programming language in either R or Python and SQL
Ability to do data analysis, reporting & visualization (Tableau, D3, etc.) at scale
Deep expertise in 

applied forecasting models (econometric time series models, tree-based methods, etc.)
building interpretable models

Effective verbal and written communications skills

What you will love about the job?


We optimize for a healthy team not only for a highly performing team. In this role you’ll interact with a diverse group of folks from Product, Software Engineering, Data and Business teams.

All CARS employees are encouraged to bring their whole, authentic self to work every day, including their talents, passions, and unique ideas.
You’ll be working with some of the brightest minds of the industry. 
Double bonus if you like talking about cars. We do too. 

This job posting is inclusive of multiple levels within our Data Science Team. Based on your background, expertise and interests, we will assess and consider you for a senior, staff or principal level role.
#LI-KO1 #LI-Remote
Senior Data Scientist Resilience Modeling at One Concern

About One Concern
One Concern brings disaster science together with machine learning for better decision-making. We quantify resilience from catastrophic perils, empowering leaders to measure, mitigate, and transfer risk. We believe that by pioneering cutting-edge science, we can make disasters less disastrous and, ultimately, build planetary-scale resilience. 

The Role 

One Concern is growing rapidly, and we are looking for a passionate, mission-driven Senior Data Scientist, Resilience Modeling to join our team.



What you will do 

Build a global-scale resilience model to predict the societal and economic impact and recovery of the built environment against disasters
Build and improve existing resilience prediction models
Work with and support domain experts and data scientists in different hazard products
Demonstrate up-to-date modeling skills (ML/statistical) and apply this to the development, execution, and improvement of action plans
Assess the potential usefulness and validity of new approaches and data sources.
Identify key problems in prediction models and propose innovative solutions.
Formulate your own problems as the problem might not always be defined for you
Collaborate with an interdisciplinary team of software engineers and data scientists on cross-functional projects, interpreting data, and translating into actionable insights



Must-haves

Ph. D. (preferred) with 2+ years or MS + 5 years industry experience in civil engineering, operation research, atmospheric sciences, statistics, mathematics, or related field.
Background in statistics, probability theory, machine learning and/or quantitative analytics
Domain knowledge and experience of natural disasters and/or risk modeling
Experience in risk model developments (machine-learning models or statistical models)
Proficient in Python



Good to have

Experience in the assessment of climate risks
Experience in community resilience modeling
Experience in large scale simulations
Experience in catastrophe risk modeling
Publication record


Compensation will be competitive with the market for this position and will include equity consideration. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, natural origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Data Science Intern at One Concern

About One Concern
One Concern brings disaster science together with machine learning for better decision-making. We quantify resilience from catastrophic perils, empowering leaders to measure, mitigate, and transfer risk. We believe that by pioneering cutting-edge science, we can make disasters less disastrous and, ultimately, build planetary-scale resilience.


The Role 
One Concern is growing rapidly, and we are looking for a passionate, mission-driven Data Science Intern to join our team. In this role, you’ll work with our data science team to build global-scale resilience models.  This is a full-time internship for a period of two to three months with the possibility of converting to full-time employment. 


What You’ll Do

Collaborate with an interdisciplinary team of software engineers and data scientists on cross-functional projects, interpreting data, and translating into actionable insights.
Assess the potential usefulness and validity of new approaches and data sources.
Build a global-scale resilience model to predict the societal and economic impact and recovery of the built environment against disasters
Build and improve existing resilience prediction models.
Work with and support domain experts and data scientists in different hazard products.
Demonstrate up-to-date modeling skills (ML/statistical) and apply this to the development, execution, and improvement of action plans.



Qualifications & Experience

Pursuing Ph. D. or M.S. in civil engineering, computer science, operation research, atmospheric sciences, statistics, mathematics, or related field.
Background in statistics, probability theory, machine learning and quantitative analytics (coursework or experiences)
Domain knowledge of natural disasters and/or risk modeling
Proficiency in Python 



Nice to Haves

Experience in the assessment of climate risks
Experience in community resilience modeling
Experience in large scale simulations
Experience in catastrophe risk modeling
Publication record


Compensation will be competitive with market for this position. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, natural origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Data Scientist Credit Risk Lending at Koho

About KOHO
KOHO is a quickly scaling FinTech company backed by leading investors and advisors from around the world. We started KOHO because we believe in doing two things:


Democratizing access to the best financial products and giving everyone a great financial foundation. 

Since our journey began 6 years ago, we’ve raised more than $340M, grown the KOHO Collective to over 200 employees, and created accounts for more than 400,000 Canadians.

About the Role

We're building a world-class financial product and we need someone to help take our data operations to the next level. Our team is growing fast, and we’re looking for a Data Scientist to join us. You understand the data-driven decision making needs of a high-growth organization and are focused on concrete outcomes and KPIs. You look for the highest leverage solution to the most important problems, through either pragmatic analysis, a predictive model, or unsupervised learning methods.


What You'll Do

Design and develop statistical models for credit risk parameters (PD, EAD, and LGD) for lending products
Assist with model deployment and monitoring, as well as re-training or updating when necessary
Coordinate and maintain communication with business stakeholders on data science-related projects
Create dashboards or conducting ad-hoc analysis to answer pertinent or urgent data-related questions
Document results, insights and methodology on a project by project basis



What You'll Bring

3+ years of experience working with data and engineering teams
Experience with retail lending products 
Experience with predictive credit risk modelling
Ability to get hands on: modelling, analysis, cleansing, documenting
Expert knowledge of Python and SQL
Strong communication skills both written and oral
Exposure to measuring business outcomes of machine learning models in production is highly valued
Experience with cloud-based platforms such as AWS or GCP
Passionate about applying data science in financial services, with ideas on how and where to improve customer’s financial lives
Experience deploying models in a production environment, and integrating them into SaaS infrastructure



Joining the (lovely!) KOHO Team
We invest time and resources into making sure KOHO is as good as the people we hire. Here are some of the reasons we attract the best people:


• Balance Your Life - Generous PTO, generous vacation, and a lifestyle spending account

• Work Anywhere - Permanently remote and $1,000 to set up your home office

• Level Up - Access to an in-house certified performance coach

• Reach Your Goals - Salary assessments twice a year, annual training allowance
• The KOHO Culture - We have won 6 "Great Place to Work ®" awards since 2019

The KOHO culture is one of collaboration, creativity, and diverse perspectives. We are committed to building and fostering an inclusive, accessible environment for everyone. If you have any questions, concerns, or requests regarding accessibility needs, please contact peopleaccessibility@koho.ca and the People and Culture team will be happy to help. 

#LI-Remote #LI-DP1
Senior Data Scientist at Pagerduty

Why We Need You:
We’re looking for a Senior Data Scientist and a proven leader passionate about building machine learning models with big data in production successfully. We expect you to collaborate with product, data-engineers and full-stack engineers to drive alignment on ML/AI-driven features at PagerDuty. If you are technical, creative, future-focused, and excited about fostering an environment amongst our engineers that helps create avenues for success and learning, then this is an excellent opportunity for you.
How You Contribute to Our Vision: Key Responsibilities

Build data driven solutions to solve business critical problems across multiple domains by developing statistical and machine learning methods on top of PagerDuty’s data infrastructure.
Work both independently and collaboratively with other data scientists, product managers, engineers, and designers to solve complex problems that deliver business value
Influence leadership to drive more data-informed decisions
Communicate, align and drive interest within the entire organization to be more data driven 
Provide guidance, technical leadership, and mentoring to other members of the team
Proactively recommend improvements and new approaches addressing potential systemic pain points and technical debt

Minimum Requirements

Graduate degree in computer science, statistics, mathematics, or related quantitative field.
You have 5+ years using machine learning and statistical analysis for building data-driven product solutions for large scale systems at the production level. 

Hands on experience in Python, SQL and other related tools.  Python is a must; C++ Java are nice to have.  Should be able develop ML features in Python for Deep Learning or Scala

Have an entrepreneurial mindset to drive research projects to completion with minimal guidance.
Strong ability to justify technical prioritization and communicate scientific work in a clear and effective manner to stakeholders, other engineers and Product
Experience working with Engineering teams ensuring a timely delivery
Solutions Data Scientist at Climate Ai

About the Role
We’re looking for a smart, passionate, team-oriented Solutions Data Scientist to support our customers in translating climate forecasts into actionable insights that matter for their business.
This person’s primary focus will be serving as the bridge between our customers and the data science team: understanding the customers needs, translating them into technical specifications, and explaining model outputs in terms of business value. This individual will have direct operational responsibilities (e.g. conducting benchmarking analyses), customer relationship responsibilities, and a project oversight role. This position will report primarily to the Solutions team,  and work closely with our data science and engineering teams to drive positive business outcomes for our customers. ClimateAi is a deep tech company, but our technology is only as valuable is the impact it has on our customers – as a Solutions Data Scientist, you will be responsible for delivering this impact.
Role Responsibilities:
Integrate ClimateAi’s forecasts into customers workflows and decision making
Analyse and understand customer data and ClimateAi insights
Translate customer needs into technical requirements
Collaborate with the data science team to deliver on those requirements via ClimateAi’s platform
Support the customer in interpreting those results and ensuring a direct link between our forecasts and their business objectives
Support business development efforts via demos, insightful analyses, and development of market-facing tools
Help build the Solutions function: define and drive processes that will enable us to scale
Grow with us: future opportunities to take on more responsibilities as our company and needs grow
Preferred Qualifications:
Domain expertise in Climate Science Meteorology, and/or Data Science, as indicated by a Master’s degree
Strong written and verbal communication skills, capable of clear communications to customers and data scientists alike
Strong project management skills: Ability to drive outcomes across teams, and in a timely fashion
Sufficient programming proficiency (Python) to execute analyses and thought partner with data science & product on new use cases and technical specifications
A good listener: able to hear and understand the customer need and the different perspectives of relevant stakeholders
Demonstrable experience in data visualization is a plus
Proficiency in Excel and Powerpoint is a plus
Most importantly, a passion for climate change solutions
Climate Data Scientist at Climate Ai

About the Role
We are a young startup, looking for a passionate candidate who can contribute to our mission to deploy impactful solutions to the most important issue of our generation. Our focus will be on developing climate adaptation & resilience tools for various sectors, with agriculture as our initial market. We are looking for a Climate Data Scientist to join our team.
The person will be conducting cutting-edge applied research at the intersection of climate and data science. This individual should be able to work remotely and independently, with an eye for detail. The position will require frequent communication with the software engineering, product and solutions teams, so an affinity for collaborative work is crucial. Expect to give and receive constructive criticism, as we are constantly re-evaluating our hypotheses and our products.
Role Responsibilities:
Conduct independent research at the intersection of weather/climate and data science
Research existing literature to identify best solutions for a given problem
Train machine learning algorithms and apply statistical techniques to weather and climate data sets
Collaborate with our software engineering, product and solutions teams to effectively develop products
Lead small team of junior data scientists
Preferred Qualifications:
MS or PhD in physical/environmental science, engineering, computer science or related
Independent research experience
Experience writing modern Python code
Experience with version control systems and Github
Desired but not required skills:
Experience with weather and climate data
Experience with modern machine learning algorithms and frameworks
Experience with customers
Data Science Intern at Climate Ai

About the Role
We are a young startup, looking for a passionate candidate who can contribute to our mission to deploy impactful solutions to the most important issue of our generation. Our focus will be on developing climate adaptation & resilience tools for various sectors, with agriculture as our initial market. We are looking for a Data Science Intern to join our team.
ClimateAi internships are full-time over a time period of at least 3 months. Interns work directly with one of our senior data scientists on cutting-edge applied research projects at the intersection of climate and data science. Interns are fully integrated into our company, including team and company-wide meetings and social activities.
We provide internship opportunities at every level of study and throughout the entire year. Internships are paid. ClimateAi is a remote company operating in the NA timezone. We welcome interns from an EU timezone, provided they are available for some evening meetings.
Desired Skills and Experience:
Enrolled in physical/environmental science, engineering, computer science or related degree
Enthusiasm to solve climate change
Coding experience, preferably in Python
Junior Data Scientist at Climate Ai

About the Role
We are a young startup, looking for a passionate candidate who can contribute to our mission to deploy impactful solutions to the most important issue of our generation. Our focus will be on developing climate adaptation & resilience tools for various sectors, with agriculture as our initial market. We are looking for a Junior Data Scientist to join our team.
The person will be developing algorithms for our climate intelligence platform and producing data analyses for our customers. This individual should be able to work remotely and independently, with an eye for detail. The position will require frequent communication with the software engineering, product and solutions teams, so an affinity for collaborative work is crucial. Expect to give and receive constructive criticism, as we are constantly re-evaluating our hypotheses and our products.
Role Responsibilities:
Develop data science algorithms for climate analytics; work in collaboration with our software engineering team to integrate the algorithms into our product.
Produce data analyses requested by our team and our customers.
Help in machine learning-driven weather and climate forecasting research.
Produce visuals to share with customers; write documentation; explain work in easily understandable way.
Required Skills and Experience:
BS in physical/environmental science, engineering, computer science or related
Ability to write well documented and structured Python code
Basic understanding of statistics
Experience analyzing and visualizing datasets
Desired but not required Skills:
Experience with version control systems and Github
Experience with weather and climate data
Experience with customers
Senior Data Scientist at Upstart

The Team
Upstart’s Machine Learning team has a direct impact on our company's success. The team consists of Research Scientists, Data Scientists, ML Engineers and other highly specialized roles who build and enable our core production models.
Because our challenges are so new, members of our Machine Learning team need strong creative problem-solving skills and the technical background to implement solutions. Our research environment affords team members the opportunity to utilize a variety of statistical and machine learning methods with the freedom and encouragement to pursue alternative approaches to solving problems. Whether developing new products or identifying novel approaches to core models, we are continuously seeking the next big ideas to move our business forward.
The Role
As a Senior Data Scientist, you'll evaluate and monitor our models, their performance, and their effects on our customers. Additionally, you'll identify potential problems or opportunities for improvement, communicate these issues to the team, and suggest solutions. This involves self-directed investigation into our business and its data, designing and preparing regular reports, as well as conducting ad hoc analyses for the Machine Learning team, company leadership, and external parties such as partner banks.
Our Machine Learning team researches and productionizes all of Upstart’s core predictive models. If data is the new oil, then you’ll be responsible for the refining process that creates the most premium fuel possible. You’ll work in an environment where actionable insights from data are valued and needed, so you’ll be able to see your analysis turn into measurable results for our company and our borrowers.


Position Location - This role is available in the following locations: Columbus or Remote (#LI-REMOTE) 


Time Zone Requirements - This team operates on either the East or West Coast time zones.


Travel Requirements - This team has regular on-site collaboration sessions six times annually split between the San Mateo or Columbus office locations. If you need to travel to make these meetups, Upstart will cover all travel related expenses.


What we’re looking for:

2+ years' in data science or related experience in a production setting
Knowledgeable in applied statistics (e.g., AB testing, hypothesis testing, linear and logistic regression)
Experience with Python or R as well as SQL 
Strong sense of intellectual curiosity balanced with humility, drive and teamwork
Numerically-savvy and smart with ability to operate at a speedy pace
Ability to quickly piece together disparate pieces of information to form a broader picture
Ability to use data to detect bugs, surprises, and other important business issues
Determination to pursue a question until reaching a satisfactory conclusion
Experience with consumer data (especially consumer finance) is a plus
Data visualization skills preferred
Enthusiasm for and alignment with Upstart’s mission and values
MS or PhD in econometrics, applied statistics or related quantitative areas of study
Intern Ai Machine Learning Research at Vimeo

Vimeo empowers video creators to tell exceptional stories and connect with their audiences and communities. Home to more than 60 million members in over 150 countries, Vimeo is the world’s largest ad-free open video platform and provides powerful tools to host, edit and share videos in the highest quality possible.
The Machine Learning Research team at Vimeo is focused on researching and deploying the latest machine learning technology to enhance all stacks of Vimeo’s products. With the massive amounts of data at Vimeo, our projects range from user insights, networking, to video understanding, and involve a wide variety of artificial intelligence (AI) techniques, such as natural language processing (NLP), image and video understanding, deep learning, and reinforcement learning.
During your internship, you will work with us to define and work on a project that’s best suited for your interest, experience and desired area of growth, as well as Vimeo’s mission. The project might vary depending on what data is available and what’s accomplishable during the length of the internship. This internship will help you adapt to real-world machine learning problems, understand the opportunities and challenges in the industry, and acquire skills and insights to conduct large-scale machine learning research projects.
What you’ll do:

Perform machine learning research utilizing datasets available on Vimeo's platform.
Conduct a full cycle of research from problem definition, to data preprocessing, investigating and optimizing potential solutions, in order to deliver models aimed at deployment.

Skills and knowledge you should possess:

Student pursuing a M.S./Ph.D with a focus on machine learning, computer science, statistics or related quantitative areas, with an expected graduation date in 2022-2023.
Strong analytical and quantitative skills, with strong programming skills and experience in Python, R or Matlab. Experience with deep learning frameworks such as TensorFlow, Pytorch.
Knowledge of deep learning with at least one of the following areas: Natural Language Processing, Computer Vision, Recommendation Systems, Search, Personalization, Reinforcement Learning.
Strong sense of ownership for one’s project, and ability to independently perform research as well as collaborate with researchers and engineers with supplemental expertise.

Bonus points:

Prior experience in publishing in top machine learning/data science conferences and journals.

While we offer competitive compensation, we don't provide accommodation. Please ensure you are interested in an internship in New York City under these circumstances before applying.
#LI-CB1