Data Scientists at Disney Entertainment Direct-to-Consumer are needed to serve as modeling and insights partners for Content, Product, Marketing, Analytics, Business Operations, and Engineering teams at Disney+, Hulu, and ESPN+. They will use data to empower decision-makers with information, predictions, and insights that influence user experiences worldwide.
Requirements
- 3+ years of experience designing, building, and evaluating practical machine learning solutions
- 2+ years of experience with a programming language for data science or statistics like Python, R, especially experience with scientific libraries like Numpy, Pandas.
- Experience with reading and writing complex SQL queries and using Databases
- Deep understanding of machine learning concepts and statistical methods
- Masters or Doctorate degree in Statistics, Econometrics, Mathematics, Computer Science, Engineering, or related field
- Excellent analytical skills and advanced level of statistics knowledge
- Familiarity with data exploration and data visualization tools such as Tableau, Looker
Responsibilities
- Design, build and improve machine learning models related to subscribers’ behavior.
- Work on the entire development process, i.e., data collection, feature engineering, algorithm development, analysis, visualization, and communicating the results.
- Collaborate with the team to productionize models.
- Drive experimentation to test the impact of the models.
- Develop comprehensive understanding of subscriber data structures and metrics.
- Mine large data sets to identify opportunities for driving growth and retention of subscribers.
- Development of prototype solutions, mathematical models, algorithms, and robust analytics leading to actionable insights, and communicating them clearly and visually.
Other
- Strong communication skills, for both technical and non-technical audiences
- Desire to collaborate with other data scientists, data engineers, analysts, and business partners
- Previous experience in marketing analytics and consumer insights, especially in the subscription services sector
- Experience developing interactive data apps using packages such as R Shiny or Streamlit
- Familiarity with data platforms and applications such as Jupyter, Snowflake, Github, Databricks, Airflow
