Lead Data Scientist

About Direct To Consumer (DTC)

Disney’s Direct to Consumer team oversees the Hulu and Disney+ streaming businesses within Disney Entertainment helping to bring The Walt Disney Company’s best-in-class storytelling to fans and families everywhere.  

The Walt Disney Company Direct to Consumer’s (DTC) Data Science team 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! 

What You'll Do

• 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. 

What To Bring

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

• 7+ years related experience with developing machine learning models and conducting 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) ​

Nice To Haves

• MS or PhD in Computer Science, Engineering, Statistics, Economics, Physics or related quantitative field (e.g. Econometrics, Mathematics, Operations Research)

• Working knowledge of Bayesian modeling and familiarity with probabilistic programming packages/language such as Stan, PyMC 

• Experience fully integrating data science solutions into the business and operationalizing ML models 

Additional Information

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