Lead Data Scientist - Disney Experiences : Job Details

About The Role & Team:

At Disney Consumer Products, we ignite imagination worldwide and are dedicated to creating joy for families and fans by offering enchanting, inspiring, and inclusive products in their everyday lives. From toys to apparel, console games, books, and beyond, our team integrates our cherished brands and franchises into the lives of families through products and experiences available globally, including digital platforms, Disney Parks, various retailers, and Disney Store locations.

The Merchandise Business Insight and Analytics (MBIA) team is a key part of Disney's Consumer Products organization, which markets and sells Disney products across the globe. The MBIA team plays a crucial role in supporting the entire retail lifecycle, providing analytics, reporting, and insights that empower a diverse community of stakeholders in areas like Category and Location Planning, Product Development, Merchandising, and Retail Operations.

We are searching for a Lead Data Scientist to spearhead advanced analytics and data science initiatives that enhance both brick-and-mortar and E-commerce retail experiences across Disney. This position will focus on developing and refining machine learning models and data-driven solutions to optimize critical areas such as customer segmentation, assortment rationalization, promotion optimization, and demand forecasting. The ideal candidate will possess extensive expertise in statistical modeling, machine learning, and retail strategy. This role is essential for facilitating data-informed decisions that improve guest experiences, boost revenue growth, and support strategic business goals across digital and physical retail environments.

This position reports to the Sr. Manager, Data Science.

What you will do:

• Lead End-to-End Model Development: Create, implement and deploy advanced statistical and machine learning models (e.g., regression, classification, clustering, time series forecasting) to tackle complex retail challenges, including customer segmentation and promotion optimization.
• Drive Scalable Data Solutions: Design and execute scalable data pipelines and model workflows using Python, SQL, and cloud platforms (e.g., Google Cloud Platform, Snowflake) for ongoing data integration and model retraining on extensive retail datasets.
• Develop Visual Analytics Tools: Create dynamic dashboards and self-service analytics solutions with tools like Tableau or Looker to track essential business metrics, assess model performance, and provide actionable insights to cross-functional partners.
• Partner with Business & Technical Stakeholders: Collaborate with product, merchandising, marketing, and technology teams to convert ambiguous business inquiries into structured analytics challenges, delivering insights that influence strategic decisions and operational enhancements.
• Mentor and Lead Data Science Best Practices: Encourage data scientists and analysts to adopt best practices in code quality, model validation, reproducibility, and responsible AI initiatives, including performance monitoring, bias mitigation, and stakeholder education.

Required Qualifications and Skills:

• 5+ years as a Data Scientist with deep expertise in retail, including customer segmentation, performance forecasting, and business optimization experience.
• Business Acumen: Ability to convert complex analytical findings into actionable strategies; history of collaborating with cross-functional teams in Merchandising, Operations, Finance, and Marketing to drive revenue outcomes.
• Retail Expertise: Proven track record of developing and refining retail strategies through advanced analytics, including customer segmentation, demand forecasting, promotional analysis, and performance evaluation across both brick-and-mortar and E-commerce channels.
• Data Visualization & Dashboarding: Skilled in creating intuitive, impactful dashboards and visual analytics using tools like Tableau, facilitating self-service insights and supporting data-driven decision-making.
• Advanced Statistical Modeling: Extensive knowledge of predictive modeling techniques, including regression, time series forecasting (e.g., ARIMA, Prophet), causal inference, and machine learning methods (e.g., XGBoost, LightGBM).
• Experimental Design: Experience in designing and analyzing experiments (e.g., A/B testing, geo-lift studies) to assess the impact of retail strategy changes.
• Python Proficiency: Advanced proficiency in Python, with a proven ability to build scalable, production-ready pricing and forecasting models using libraries such as pandas, scikit-learn, statsmodels, and PyMC.
• SQL Expertise: Advanced skills in SQL for querying and manipulating large-scale retail and transactional datasets, along with experience creating automated data pipelines.
• Big Data & Cloud Proficiency: Practical experience with large-scale data environments on platforms like Google Cloud Platform (GCP), Snowflake, BigQuery, and Spark for efficient data processing and analysis.

Education:

• Bachelor's degree in Mathematics, Economics, Data Science, Computer Science, Operations Research, or a related field, and/or equivalent work experience.

Preferred Education:

• Master of Science or PhD.

Additional Information:

This role is located in Orlando, FL.

Benefits and Perks: Disney provides a rewarding package to help you lead your best life, featuring health and savings benefits, educational opportunities, and unique extras that only Disney offers.