About the job
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.
Responsibilities
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
Qualifications
Minimum
3+ years of data scientist experience
Preferred
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)