Lead Data Scientist - Experimentation at Disney Direct to Consumer Santa Monica, CA

Disney Direct to Consumer; Santa Monica (CA); Vor Ort; USD 152.200 - 204.100; Vollzeit

Benefits dieser Stelle

Bonus and/or long-term incentives

Zusammenfassung

Disney Direct to Consumer is looking for a Lead Data Scientist to transform complex data into strategic business decisions that shape the future of streaming entertainment.

You will design experiments, apply causal inference methods, and build scalable solutions to optimize subscriber journey. Ideal candidates have a strong statistical background, leadership experience, and be able to communicate findings to executive stakeholders.

This position is based in Santa Monica, CA with compensation ranging up to $204,100 per year.

Qualifikationen

• 7+ years of experience conducting strategic analyses and communicating insights to drive decision-making.
• Expertise in Python, R, or similar languages for statistical analysis.
• Strong background in statistical modeling techniques.

Aufgaben

• Lead end-to-end A/B testing initiatives and Geo Experiments.
• Leverage advanced causal inference techniques to extract actionable insights.
• Develop scalable experimentation and causal inference tools.

Kenntnisse

Statistical modeling

Python

SQL

Causal inference

Data analysis

Machine Learning

Ausbildung

Bachelor’s degree in advanced Mathematics, Statistics, Data Science or comparable field

Tools

Jupyter

Databricks

Snowflake

Github

Jobbeschreibung

Job Summary

Join Disney's Direct to Consumer Experimentation and Causal Inference Data Science team as a Lead Data Scientist, where you'll transform complex data into strategic business decisions that shape the future of streaming entertainment.

Collaborating closely with cross‑functional partners across the Business, you'll architect and execute sophisticated experiments that optimize every aspect of the subscriber journey—from initial acquisition through long‑term retention and revenue growth.

As part of Disney's rapidly evolving streaming ecosystem, you'll tackle complex business challenges that directly impact millions of subscribers across Disney+, Hulu, and ESPN. Your insights will shape Product roadmaps, pricing strategies, and user experience optimizations that drive measurable business growth.

What You’ll Do

• Design and Execute Experiments: Lead end‑to‑end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations.
• Apply Causal Inference Methods: Leverage advanced techniques including difference‑in‑differences, instrumental variables, propensity score analysis, and other quasi‑experimental designs to extract actionable insights from observational data.
• Build Scalable Solutions: Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses.
• Deliver Strategic Insights: Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations.
• Drive Innovation: Be a thought leader on robust and rigorous analysis throughout the Data Intelligence and Analytics team.
• Influence Executive Decisions: Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non‑technical stakeholders.

Minimum Qualifications

• Bachelor’s degree in advanced Mathematics, Statistics, Data Science or comparable field of study.
• 7+ 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.
• Highly collaborative with excellent written and verbal communication skills and demonstrated experience presenting directly to Executive stakeholders.
• 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.
• Exceptional curiosity and a drive for insights that impact business outcomes.

Preferred Qualifications

• Masters or PhD in a quantitative field with an emphasis on experimentation or causal inference.
• Experience applying strategic thinking to analyze market trends and consumer insights, with preference for candidates who have worked with subscription‑based business models.
• Ability to adapt quickly in a fast‑moving environment with shifting priorities.
• Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github.

The hiring range for this position in Santa Monica, CA and Glendale, CA is $152,200 - $204,100 per year, in NYC area is $159,500-$213,900, and in San Francisco area $166,800-$223,600. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job‑related knowledge, skills, and experience among other factors. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.