Data Scientist II - Segmentation Data Science

Data scientists at Disney Entertainment Direct-to-Consumer are the modeling and insights partners for the Content, Product, Marketing, Analytics, Business Operations, 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.

• Modeling:
  Design, build and improve machine learning models related to subscribers’ behavior. Work through data collection, feature engineering, algorithm development, analysis, visualization, and communicating results. Collaborate to product ionize models and drive experimentation.
• Deep analysis:
  Develop comprehensive understanding of subscriber data structures and metrics. Mine large data sets to identify opportunities for driving growth and retention of subscribers.
• Visualization of complex data sets:
  Develop prototype solutions, mathematical models, algorithms, and robust analytics leading to actionable insights and communicating them 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.

• Bachelor’s degree in advanced mathematics, statistics, data science or a comparable field of study.
• 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 such as Python or R, especially experience with scientific libraries like Num Py and Pandas.
• Experience with writing complex SQL queries and working with databases.
• Deep understanding of machine learning concepts and statistical methods.
• Strong communication skills for both technical and non‑technical audiences.
• Desire to collaborate with other data scientists, data engineers, analysts, and business partners.

• Master’s or Doctorate degree in statistics, econometrics, mathematics, computer science, engineering, or a related field.
• Previous experience in marketing analytics and consumer insights, especially in the subscription services sector.
• Excellent analytical skills and advanced level statistics knowledge.
• Familiarity with data exploration and visualization tools such as Tableau or Looker.
• Experience developing interactive data apps using packages such as R Shiny or Streamlit.
• Strong expertise with Python and libraries such as scikit-learn and Sci Py.
• Familiarity with data platforms and applications such as Jupyter, Snowflake, Git Hub, Databricks, and Airflow.

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