The Walt Disney Company

Data Analyst – Observational Causal Inference

The Walt Disney Company

full-time

Posted on:

Origin:  • 🇺🇸 United States • California, New York

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Salary

💰 $99,900 - $133,900 per year

Job Level

Mid-LevelSenior

Tech Stack

CloudPythonSparkSQLTableau

About the role

  • Apply advanced analytics techniques (data mining, data visualization, statistical analysis, causal inference, regression, machine learning, time-series forecasting) to large-scale, high-dimensional data in order to inform global business decisions
  • Analyze customer behavior (e.g., genre preferences, viewing patterns) to identify unmet customer needs and untapped content opportunities
  • Use advanced causal inference methodologies to quantify engagement and overall impact of sharing title licenses with internal and external platforms
  • Predict content engagement to help guide acquisition decisions
  • Optimize our content launch and episode release strategy
  • Test merchandising strategies to optimize engagement and retention
  • Ideate and develop new metrics and KPIs, measuring content performance, engagement and churn for strategic decision-making
  • Support complex projects, workstreams, and new initiatives & capabilities. This includes scoping out the breadth & depth of a project, helping manage the time & resources available, adapting plans to meet evolving needs and operational challenges, and representing the product with business partners and executive leadership
  • Maintain relationships with stakeholders while understanding their needs and providing them with rapid and robust solutions to their requests
  • Provide ad-hoc analysis support for stakeholders to help move the business forward
  • Effectively communicate actionable results through compelling data storytelling across the organization

Requirements

  • Bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, Applied Economics, or a related field.
  • 3+ years of experience in analytics, machine learning model development, and data analysis using Python and/or R.
  • Proficient in querying cloud-hosted databases with SQL and engineering data solutions using technologies like Databricks, S3, and Spark.
  • Applied expertise in observational causal inference methods (e.g., difference-in-difference, propensity score matching) for non-experimental settings.
  • Skilled in statistical and machine learning techniques including time-series forecasting, regression, decision trees, and clustering.
  • Strong data storytelling abilities across verbal, written, and visual formats.
  • Effective communicator with both technical and non-technical audiences, capable of explaining model behavior and algorithmic decisions.
  • Familiar with data exploration and visualization tools such as Looker, Tableau, and JupyterLab/Notebook.
  • Demonstrated independence and creativity in solving open-ended problems.