Disney Streaming Services is responsible for developing and operating The Walt Disney Company's direct-to-consumer video businesses globally, including the ESPN+ premium sports streaming service; Disney+, the dedicated streaming home for entertainment from Disney, Pixar, Marvel, Star Wars, National Geographic and BAMTECH Media, a global leader in direct-to-consumer video streaming products and solutions. Our core mission is to deliver global audiences the freedom to access content on their terms across any connected device, time or location. We serve consumers by bringing the world's most beloved characters, timeless stories, legendary athletes, and epic sporting events to global audiences through best-in-class direct-to-consumer video services. We strive daily to imaginatively challenge convention with innovative technology that gives consumers the freedom to access content on their terms across any connected device, time or location.
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

• Modeling: Design, build and improve machine learning models. Work end to end from data collection, feature generation and selection, algorithm development, forecasting, visualization and communicating of model results. Collaborate with engineering to productionize models. Drive experimentation to test impact of model based optimization.
• Deep analysis: Develop comprehensive understanding of subscriber and payment data structures and metrics. Mine large data sets to identify opportunities for driving growth and retention of subscribers.
• Visualization of Complex Data sets: Development of prototype solutions, mathematical models, algorithms, and robust analytics leading to actionable 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.

Basic Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, Mathematics, Physics, Econometrics, or Statistics
• 2+ years of experience designing, building, and evaluating practical machine learning solutions
• Strong coding experience in one (or more) data programming languages like Python/R, additional experience with scientific libraries like Numpy, Pandas, or equivalent libraries a plus
• Proficient in analyzing data and developing ML models using Python (with ML frameworks like tensorflow, scikit-learn, etc.)
• Strong background in statistical modeling: regression, classification, causal inference, and particularly in time series analysis and forecasting
• Experience developing scalable mathematical models and solving complex quantitative problems that can be understood by non-mathematical colleagues
• 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
• Good understanding of SQL

Preferred Qualifications

• Advanced degree in a quantitative discipline
• Excellent analytical skills, advanced level of statistics knowledge
• Demonstrated skills in selecting the right statistical tools given a data analysis problem
• Ability to adapt quickly in a fast-moving environment with shifting priorities
• Strong communication skills, for both technical and non-technical audiences
• Ability to handle multiple tasks concurrently and in a timely manner
• Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Airflow, Github
• Familiarity with designing and analyzing A/B testing and other experiment types

• Experience thinking strategically to interpret market and consumer information, preferably about a subscription service
• Some experience with distributed data technologies (Hive, Spark)