Join a newly created team dedicated to the Disney+ Subscriber Perks program, where you'll transform complex data into strategic business decisions that shape the future of our perks program. Collaborating closely with cross-functional partners in Commerce, Product, Marketing, and Engineering, you'll architect and execute sophisticated experiments that optimize every aspect of our perks program—from initial acquisition through long-term engagement with subscriber perks.

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, user experience optimizations, and partnership decisions 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, and quasi-experimental designs to extract actionable insights from observational data

• Drive Strategic Insights: Partner with Product, Marketing, Partnerships, and Finance teams to identify optimization opportunities and translate complex analytical findings into clear business recommendations

• Influence Executive Decisions: Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders

• Build Scalable Solutions: Develop automated experimentation pipelines, causal inference framework, and user-facing tools that can scale across marketing platforms

Required Qualifications & Skills

• Strong programming skills in R, Python, or similar languages.

• Expertise in using SQL to explore and analyze large data sets.

• Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Redshift, Airflow.

• Experience with data visualization tools (e.g. Tableau, Power BI, Looker, Plotly, etc.).

• Demonstrates strong strategic and analytical thinking, with the ability to interpret market and consumer data, translate complex analyses into clear, actionable insights, and effectively communicate opportunities and challenges to diverse stakeholders.

• Familiarity with experimentation design and analysis.

• Proven ability to manage end-to-end causal inference analyses, from initial requirements to impactful outcomes.

• Practical experience and expertise in applied statistics and data science methodologies (general advanced data modeling and predictive analytics e.g., multivariate regression analysis, machine learning, deep learning, forecasting, Bayesian estimation, causal inference).

• Strong ability to build relationships with teammates, business partners, and technical colleagues.

• Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Redshift, Airflow.

Preferred Qualifications

• Exposure to version control tools like Git.

• Experience in the streaming media industry and/or supporting a direct-to-consumer subscription-based product.

• Experience with distributed databases and query languages like Spark and Scala.

• Experience with Streamlit or React web development.

• Familiarity with using or building Gen AI solutions for productivity and efficiency gains.

Required Education

• Bachelor's degree in Data Analytics, Computer Science, Data Engineering, Mathematics, Statistics, or comparable field of study, and/or equivalent work experience.

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The hiring range for this position in New York, NY is $84,500 to $113,300.00 and in Santa Monica, CA and Glendale, CA is $80,700 to $108,100. 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.