Data Scientist
San Francisco, CA
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingJoin the Monetization team at Twitch, where we build the products that help creators make a living on the platform.
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.
You'll work on products like Subscriptions, Bits, and Gifting, and the pricing and packaging decisions behind them.
From the employer’s posting
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.
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.
Education & alternatives
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
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)
Tools in this posting
- Python
- SQL
- SageMaker
- Airflow
- R
Source — Tool mentions in context
- Proficiency in SQL - Proficiency with Python or R - Strong foundation in experimentation and causal inference, including A/B test design and quasi-experimental methods
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
- 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
- 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)
Benefits in the posting
Full benefits wording- 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.
- 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.
From the employer’s posting.
About Twitch
Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more.
In the employer’s words · Read in context
Job description
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.
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.
Twitch 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.
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Source & posting history
Source notes
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- Pay
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- Location & working pattern
San Francisco, CA
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- Status in our records
- Active
- First seen by us
- Jul 9, 2026
- Recorded sightings
- 39
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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