Data scientists at Disney Streaming Services are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney+, Hulu and ESPN+. They use data to empower decision-makers with information, predictions, and insights that ultimately influence the experiences of millions of users worldwide. Scientists on the team build models, perform statistical analysis, and create visualizations to provide scalable, persistent capability that is iteratively improved through direct interaction with cross-functional business partners.
WHAT YOU'LL DO
• 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.
WHAT TO BRING
• Master's degree in a quantitative field (e.g. Computer Science, Engineering, Mathematics, Physics, Operations Research, Econometrics, Statistics)
• 7+ years of experience designing, building, and evaluating practical machine learning solutions
• 7+ years of experience with statistical programming language (e.g. Python, Spark, PySpark) and database languages (e.g. SQL)
NICE TO HAVES
• Doctorate degree in a quantitative discipline
• Excellent analytical skills, advanced level of statistics knowledge
• Strong expertise with Python and libraries such as scikit-learn, SciPy
• Familiarity with Bayesian modeling and probabilistic programming packages such as PyMC
• Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Airflow, Github
• Familiarity with data exploration and data visualization tools such as Tableau, Looker
• Familiarity with designing and analyzing A/B testing and other experiment types
• 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, including large and complex ones
• Demonstrated leadership experience, including people and project management
Jobcode: Reference SBJ-rjv4n2-52-205-167-104-42 in your application.