Data Scientist

Twitch
New York, NY
On-site

Who this role is best for

Best suited to mid-level data scientists with strong causal inference skills working in consumer product monetization.

Best fit for

  • Economists or statisticians transitioning into tech product roles.
    — “strong economics or causal ML foundation
  • Data scientists comfortable with imperfect data and stakeholder collaboration.
    — “working with imperfect data, and partnering with stakeholders
  • Professionals experienced in high-volume subscription or marketplace products.
    — “consumer products with high transaction volume

Things to consider

  • Requires proficiency in both SQL and Python/R for analysis.
    — “Proficiency in SQL, Proficiency with Python or R
  • Must be comfortable with quasi-experimental methods when A/B tests aren't feasible.
    — “apply causal inference methods where experimentation isn't feasible

How to stand out

  • Showcase production ML deployments beyond academic projects.
    — “deploying ML models in production
  • Highlight specific pricing strategy impacts from past roles.
    — “pricing, segmentation, and revenue optimization
  • Demonstrate cross-functional collaboration with finance/engineering teams.
    — “Partner with product, engineering, and finance
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · CompanyLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • informing pricing and segmentation decisions
  • designing and analyzing experiments
Typical background
data scienceeconomicscausal ML

Skills & requirements

Required

Causal InferenceSQLPython Or RA/B TestingDashboard Building

Preferred

AirflowSagemakerModern Causal ML Methods

Stack & domain

SQLPythonRAirflowSagemakerMl ModelsCommunicationTeamworkProblem-solvingData ScienceEconomicsCausal MlConsumer ProductsHigh Transaction Volume

About the role

Original posting from Twitch via Greenhouse

About Us

Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.

We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X,  and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.

About the Role

Join the Monetization team at Twitch, where we build the products that help creators make a living on the platform. You'll work on products like Subscriptions, Bits, and Gifting, and the pricing and packaging decisions behind them. 

You'll partner closely with product, engineering, finance, and data teams to measure the impact of new features, design and analyze experiments, and apply causal inference methods to inform decisions where A/B testing isn't possible. The work ranges from high-velocity experimentation on consumer-facing products to deeper pricing, policy, and segmentation analyses where causal identification is the central challenge.

This role is well-suited for someone with a strong economics or causal ML foundation who wants to apply rigorous statistical thinking to real product decisions at scale. You'll need to be comfortable writing SQL, working with imperfect data, and partnering with stakeholders to turn analysis into product impact. Our team is based at Twitch HQ in San Francisco, CA.

You can work in San Francisco, CA; New York, NY; or Seattle, WA 

You Will:

Apply causal inference methods where experimentation isn't feasible

Develop models and analyses that inform pricing, segmentation, and revenue optimization

Design, run, and analyze A/B experiments 

Partner with product, engineering, and finance to translate ambiguous business questions into measurement frameworks

Build and maintain dashboards, reporting, and analytical tooling that support ongoing decision-making

You Have:

3+ years of experience as a data scientist, applied scientist, economist, or related field; OR a PhD in Economics, Statistics, Computer Science, or related quantitative field

Proficiency in SQL

Proficiency with Python or R

Strong foundation in experimentation and causal inference, including A/B test design and quasi-experimental methods

Strong communication skills across technical and non-technical stakeholders

Comfort building dashboards and recurring reporting

Bonus Points

Master's or PhD in Economics, Statistics, or a related quantitative field

Industry experience working on consumer products with high transaction volume (subscriptions, marketplaces, payments) 

Hands-on experience with Airflow, SageMaker, or deploying ML models in production

Familiarity with modern causal ML methods (double ML, causal forests, heterogeneous treatment effects)

Perks

Medical, Dental, Vision & Disability Insurance

401(k)

Maternity & Parental Leave

Flexible PTO

Amazon Employee Discount

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 

Job ID: TW9226

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

US, WA, Seattle - Annually$136,000—$184,000 USDThe base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

US, CA, San Francisco - Annually $157,300—$212,800 USDUS, NY, New York - Annually$153,400—$207,500 USDTwitch is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Twitch values your privacy. Please consult our Candidate Privacy Notice, for information about how we collect, use, and disclose personal information of our candidates.

Source: Twitch careers (Greenhouse)

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