About the RoleJoin 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 USD
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, CA, San Francisco - Annually
$157,300-$212,800 USD
US, NY, New York - Annually
$153,400-$207,500 USD
