Job Description

Job Summary:

Join Disney's Direct to Consumer Experimentation and Causal Inference Data Science team as a 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 in Commerce, Product, Marketing, and Engineering, 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. 

Job Summary:

We’re looking for a Data Scientist to join the Experimentation & Causal Inference team within Disney’s Direct to Consumer segment . In this role, you’ll transform complex data into actionable insights, helping to optimize the entire subscriber journey—from acquisition and engagement to retention and monetization. You’ll collaborate closely with partners across Product, Marketing, Commerce, and Engineering to design high-impact experiments and develop causal models that drive measurable business outcomes.

Responsibilities and Duties of the Role:

• Design and lead A/B tests and geo experiments from hypothesis to recommendation
• Apply causal inference methodologies such as difference-in-differences, instrumental variables, and quasi-experimental designs to extract insights from observational data
• Translate findings into clear, impactful recommendations for cross-functional stakeholders
• Build scalable experimentation and analysis pipelines that can be leveraged across multiple products and teams
• Present results to executive stakeholders and communicate complex statistical concepts in a compelling and accessible way
• This person may work out of our New York City, San Francisco, or Santa Monica office.

Required Education, Experience/Skills/Training:

Basic Qualifications:

• Proficiency in Python and strong SQL skills for working with large datasets
• Experience designing and analyzing A/B and geo experiments
• Familiarity with causal inference techniques such as difference-in-differences and instrumental variables
• Applied knowledge of statistical methods and predictive modeling
• Ability to translate complex data into actionable business insights
• Strong communication and collaboration skills across technical and non-technical teams

Preferred Qualifications:

• Prior experience supporting a direct-to-consumer or subscription-based digital product
• Familiarity with distributed computing frameworks and tools such as Spark, Scala, or Hadoop
• Hands-on experience with modern data platforms and tools such as Databricks, Snowflake, Redshift, Jupyter, or Airflow

Required Education:

• Bachelor’s degree in advanced Mathematics, Statistics, Data Science or comparable field of study, and/or equivalent work experience

The hiring range for this position in New York City is $99,900 - $133,900, and in San Francisco, it is $104,400 - $140,000. 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

Job Tags

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