Data Scientist II

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 outstanding direct-to-consumer video services.

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 phenomenal role for you!

Responsibilities

• Support the streaming business with machine learning and statistical modeling focused on understanding and predicting subscriber behavior, such as churn, upgrade/downgrade, price sensitivity, user segmentation, survival analysis, experimental design and analysis, and causal inference
• Develop and implement innovative Machine Learning techniques to answer key business questions while identifying new areas to explore
• Drive experimentation to evaluate the impacts of your models
• Partner closely with team members across the organization to identify and unlock opportunities. You will also collaborate with other data teams to improve platform capabilities around data modeling, data visualization, experimentation and data architecture
• Present your recommendations to senior executives

Basic Qualifications

• Bachelors or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Econometrics, or Statistics
• 3+ 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, time series forecasting, causal inference, and other techniques
• Experience developing scalable mathematical models and solving sophisticated quantitative problems that can be understood by non-mathematical colleagues
• Ability to draw insights and conclusions from data to advise model development and business decisions
• Desire to partner with other data scientists, data analysts, and key business partners
• Good understanding of SQL

Preferred Qualifications

• Advanced degree in a quantitative field
• Excellent analytical skills, advanced level of statistics knowledge
• Proven skills in selecting the right statistical tools given a data analysis problem
• Ability to adapt quickly in a fast paced environment with shifting priorities
• Strong interpersonal skills, for both technical and non-technical audiences
• Ability to prioritize 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
• Experience with distributed data technologies (Hive, Spark)
• Experience with NLP and NN models

The hiring range for this position in New York, NY is $117,998 to $158,290 and in Santa Monica, CA is $112,586 to $151,030 per year. 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.