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Twitch

Data Scientist

Twitch
San Francisco, CA $136k - $213k/yr Full time Posted 4d ago
A/B Testing Analytics AWS Business Intelligence Causal Inference Data Analysis Data Analytics Data Pipeline Data Science Data Visualization Prescriptive Analytics Reporting and Analytics Revenue Modeling SQL Statistical Modeling
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Job Description

At Twitch, the Monetization team is expanding its quantitative toolkit to sharpen pricing, segmentation, and revenue optimization. The Data Scientist will apply economics and causal inference to inform product decisions, partnering with product, engineering, and finance to turn ambiguous questions into measurable experiments and actionable insights. A solid foundation in causal ML, fluency in SQL, and programming in Python or R are essential to translate data into strategies in a fast-paced environment.

Responsibilities

  • Apply causal inference methods when controlled experiments aren’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

Requirements

  • 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

Technologies

  • SQL
  • Python
  • R
  • Airflow
  • SageMaker

Benefits

  • Medical, Dental, Vision & Disability Insurance
  • 401(k)
  • Maternity & Parental Leave
  • Flexible PTO
  • Amazon Employee Discount

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 (DoubleML, causal forests, heterogeneous treatment effects)

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