Hybrid Senior Data Scientist – Experimentation, Causal Inference

at The Walt Disney Company

• Job title: Senior Data Scientist – Experimentation, Causal Inference
• Job type: Full Time
• Experience level: Senior
• Salary: $141,900 - $190,300 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Python, Scikit-Learn, SQL
• Location requirements: Hybrid, New York City, United States

About the role

• Sr Data Scientist at Disney shaping strategic business decisions for streaming services. Collaborating cross-functionally to optimize subscriber journey through data-driven insights.

Responsibilities

• Join Disney's Direct to Consumer Experimentation and Causal Inference Data Science team as a Sr Data Scientist
• Transform complex data into strategic business decisions that shape the future of streaming entertainment.
• Collaborate closely with cross-functional partners across the Business
• Architect and execute sophisticated experiments that optimize every aspect of the subscriber journey—from initial acquisition through long-term retention and revenue growth.
• Tackle complex business challenges that directly impact millions of subscribers across Disney+, Hulu, and ESPN.
• Shape Product roadmaps, pricing strategies, and user experience optimizations that drive measurable business growth.
• Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations
• Leverage advanced techniques including difference-in-differences, instrumental variables, propensity score analysis, and other quasi-experimental designs to extract actionable insights from observational data
• Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses.
• Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations.
• Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders.

Requirements

• Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field.
• 5+ years of experience conducting strategic analyses and communicating insights to drive decision-making.
• Expertise in Python, R, or similar languages, including experience building software packages for statistical analysis.
• Expertise in SQL.
• Proficient in analyzing data and developing ML models using Python (with ML frameworks like LGBM, scikit-learn, etc.).
• Strong background in statistical modeling: regression, classification, time series forecasting, causal inference, and other techniques.
• Demonstrated ability to translate complex data into clear and actionable narratives, and the ability to communicate opportunities and challenges to multiple stakeholders.
• Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling.
• Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches.
• Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes.

Benefits

• A bonus and/or long-term incentive units may be provided as part of the compensation package
• Full range of medical, financial and/or other benefits, dependent on the level and position offered