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: 

The Data Science team at Disney Streaming Services combines deep data analysis and research of our rich user data to present a compelling vision around user retention and preferences across the vast ecosystem of our product offerings and content. We are the insights and modeling partners for the content, marketing, product, and engineering teams at Disney+, Hulu and ESPN+. As Data Scientists, we use data to empower decision-makers with information, predictions, and insights that ultimately influence the experiences of millions of users worldwide. If you are someone who loves to work cross-functionally, build models, perform statistical analysis, and create visualizations to provide scalable and iterative capabilities, then this is a fantastic role for you!

Responsibilities and Duties of the Role: 

• Modeling: Apply state of the art machine learning and statistical analysis to develop models related to opportunity sizing, targeting, and optimization.
• Deep analysis: Analyze user behavioral data to identify patterns, uncover opportunities, and create common understanding of how people are interacting with the service and content.
• Visualization of Insights: Development of prototype solutions, mathematical models, algorithms, and robust analytics leading to impactful insights communicated clearly and visually.
• Partnership: Partner closely with business stakeholders to identify and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, data visualization, experimentation and data architecture.

Required Education, Experience/Skills/Training: 

Basic Qualifications:

• Experience with developing machine learning models and statistical analysis
• Deep understanding of machine learning concepts and statistical methods
• Ability to draw insights and conclusions from data to inform model development and business decisions
• Desire to collaborate with other data scientists, data analysts, and key business partners
• Proficient in analyzing data and developing ML models using Python (with ML frameworks like tensorflow, scikit-learn, etc.)
• Capable of reading and writing Object-Oriented code to review and implement modeling pipelines (Airflow, Luigi, etc.)
• Understanding of SQL and distributed data technologies (Hive, Spark)

Preferred Qualifications:

• Working knowledge of Bayesian modeling
• Experience fully integrating data science solutions into the business and operationalizing ML models

Required Education:

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