The Walt Disney Company
Associate Data Scientist
The Walt Disney CompanyUnited States14 hours ago
Full-timeEngineering, Information Technology
Would you like to be part of the interdisciplinary team providing vital insights into the rapidly evolving media landscape for Disney’s suite of television networks (ABC, ESPN, etc.) and direct-to-consumer (DTC) streaming services? Join our Data & Analytics Operations team, whose mission is to develop, support, and improve analytics operations by delivering data-driven applications that drive efficiencies across the Research, Insights & Analytics group in Disney Entertainment (DE).

We highly value statistical modeling and machine learning approaches—including cross-media measurement and activation across linear, streaming, and digital platforms. We balance advanced methods with pragmatic, classical ones that focus on strong business context, merging the science with the craft. Additionally, we incorporate and deploy modern GenAI-assisted workflows to accelerate analysis and documentation within established privacy and governance standards.

Job Summary

As a Data Scientist on the Disney Entertainment (DE) Research, Insights & Analytics team, you’ll develop and improve predictive models that inform advertising and audience dynamics across Disney’s television networks and DTC streaming services (Disney+, Hulu, ESPN+). Primary focus will be viewership and impressions forecasting—built in partnership with Linear and Digital forecasting teams—to optimize Ad Sales yield and support the DTC and Linear P&Ls. You’ll extend this work into cross-media measurement and activation as a whole, delivering clear communications of model accuracy, results, and business impact.

You’ll contribute to production-level data-science pipelines and monitoring of models (clean, well-tested Python/SQL; versioning, and QA) and help enhance analysis of complex data for partners in Research, Content, Ad Sales, and Forecasting. You’ll responsibly leverage and deploy AI workflows to improve quality, speed, and depth of analysis—validating outputs before use.

Responsibilities And Duties Of The Role

  • Machine Learning and Statistical Modeling: Design and develop predictive and generative model pipelines by leveraging classical data science and modern AI/ML to impact and measure KPIs; analyze drivers of change and implement improvements that enhance accuracy and stability of cross-media measurement and advance analytics.
  • Data Quality: Ensure data is clean and trustworthy; investigate and escalate anomalies; perform robust feature engineering and data prep across linear and streaming sources; contribute to source-of-truth definitions.
  • Applications and Communications: Build visualizations and applications to share results with business stakeholders in an easily digestible, sustainable, and automated manner; Analyze data to identify patterns and uncover opportunities.
  • Collaboration: Partner closely with peers and business stakeholders to identify and unlock opportunities. Collaborate with other data teams to improve capabilities around data modeling, data platforms, and data visualizations.
  • Process Improvement: Drive innovation by exploring new statistical techniques and brainstorming ways to optimize existing infrastructure and make processes even better.
  • Operations: Apply Agile principles via participating in standups, sprint planning, writing business requirements documents, and retrospectives; Participate in an “Open Source” learning environment where sharing, documenting, teaching, and collaborating with others is the culture.

Required Education, Experience/Skills/Training

Basic Qualifications:

  • Proficiency in SQL and Python (e.g., pandas, numpy, scikit-learn) for data analysis.
  • Experience designing and implementing predictive models (e.g., regression, time series, decision trees, XGBoost, clustering).
  • Experience working with Git and collaborative development practices.
  • Experience with data visualization tools and applications (e.g. Tableau, plotly, Streamlit)
  • Ability to communicate clearly with technical and non-technical audiences.
  • User/Client orientation; strong interpersonal skills that build trust across teams.
  • Comfort with messy data and flexibility in dynamic environments.
  • Experience responsibly using AI-assisted workflows with validation.

Preferred Qualifications

  • Experience with ETL, data pipeline management, and cloud infrastructure for managing large amounts of data (e.g. AWS, PySpark, Snowflake, Airflow, Databricks);
  • Experience using web frameworks (Django) and JavaScript libraries (ReactJS, JQuery) to build professional frontend and backend web applications focused on user experience;
  • Experience building internal tools that help teams operationalize analytics (e.g., small Streamlit/Gradio utilities, scheduled batch jobs).
  • Exposure to managed LLM/AI services inside analytics platforms is a plus.

Required Education

  • A Bachelor’s Degree in Computer Science, Statistics, Data Science, Mathematics, Econometrics, Cognitive Science, or equivalent substitute.

The hiring range for this position in New York, NY is $102,100 to $136,900 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.

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