Professional Intern – Data Science

Job Description

Commercial Data Science Intern, Fall 2026 | Walt Disney World

The Tone:
This is an internship at Walt Disney World, located in Orlando, FL. Walt Disney World’s Commercial Strategy organization is dedicated to putting its data assets to work, applying quantitative techniques to uncover new insights about Guests and the business. This role contributes directly to shaping and improving Disney products and offerings by enabling the creation of holistic models and informing major commercial decisions. A position like this highlights highly-technical data science skills in the midst of the company’s main commercial strategy.

The TL;DR
• Role: Internship
• Type: Full-time, 40 hours each week
• Location: In-person, Orlando, FL
• Pay: $42 hourly
• Team: Professional Intern – Data Science reports to the Manager of Data Science.
• Mission: Apply quantitative techniques to data assets to discover previously unknown insights about Guests and the business, helping form and improve Disney products and offerings.
• Tech Stack: SQL, Python, R, NoSQL databases, Snowflake, Git, Sagemaker, Dataiku, Tableau, Docker, Kubernetes, TensorFlow, Spark MLlib, PyTorch, scikit-learn, Keras, AWS, Google Cloud, Azure

What You’ll Actually Do
• Data Wrangler: Translate business and analytic needs into data requirements, collaborating with technology partners to troubleshoot data quality issues.
• Data Wrangler: Compile and cleanse complex data across various domains to establish a strong foundation for analytical work.
• Analytics Creator: Conduct end-to-end analysis, encompassing data collection, exploration, feature generation, reduction, and algorithm selection.
• Analytics Creator: Determine the most efficient and effective statistical, predictive, and prescriptive techniques to solve business problems.
• Insights Translator: Interpret analytical outputs and model results to draw inferences, quantify uncertainty, and provide actionable business recommendations.

The Must-Haves
• Background: Currently enrolled undergraduate student pursuing a degree in a quantitative field such as statistics, mathematics, econometrics, or data science.
• Experience: Experience performing data manipulation, engineering, or analysis using SQL, Python, or R. Familiarity with SQL or NoSQL databases and data modeling techniques and best practices.
• Skills: Knowledge of industry-leading data and analytic tools including Snowflake, Git, Sagemaker, Dataiku, and Tableau. Ability to follow existing programming and style guidelines to maintain consistent code quality. Strong communication and interpersonal skills, with the fortitude to achieve results.
• Bonus: Familiarity with Docker and Kubernetes. Experience with Machine Learning concepts and using ML frameworks and libraries such as TensorFlow, Spark MLlib, PyTorch, scikit-learn, or Keras. Experience with cloud platforms such as AWS, Google Cloud, or Azure, as well as big data technologies.