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Overview
About The Role & Team: At Disney Consumer Products, we inspire imagination around the world and are committed to creating happiness for families and fans by bringing captivating, inspiring, and inclusive products into their daily lives. Our team brings brands and franchises into the lives of families through products and experiences found worldwide, such as the Disney Store e-commerce platform, Disney Parks, retailers, and Disney Store locations. The Merchandise Business Insight and Analytics (MBIA) team supports the full retail lifecycle by providing analytics, reporting, and insights that empower data-informed decision-making for stakeholders across Category and Location Planning, Product Development, Merchandising, and Retail Operations. We are seeking a
Sr. Data Scientist
to support and drive advanced analytics and data science initiatives for brick-and-mortar and ecommerce retail across Disney Experiences. This role focuses on developing and enhancing machine learning models and data-driven solutions to optimize customer segmentation, assortment rationalization, promotion optimization, and performance forecasting. The ideal candidate will have deep expertise in statistical modeling, machine learning, and retail strategy, enabling data-informed decisions that enhance guest experience and drive revenue growth across digital and physical retail environments. This role will report to the Sr. Manager, Data Science. What you will do
Lead End-to-End Model Development: Design, develop, and deploy advanced statistical and machine learning models (e.g., regression, classification, clustering, time series forecasting) to solve complex retail problems including customer segmentation, promotion optimization, and demand forecasting. Drive Scalable Data Solutions: Architect and implement scalable data pipelines and model workflows using Python, SQL, and cloud platforms (e.g., Google Cloud Platform, Snowflake) to support continuous data integration and model retraining across large-scale retail datasets. Develop Visual Analytics Tools: Build dynamic dashboards and self-service analytics solutions using Tableau, Looker, or similar platforms to monitor key business metrics, track model performance, and deliver actionable insights to cross-functional partners. Partner with Business & Technical Stakeholders: Collaborate with product, merchandising, marketing, and technology teams to translate ambiguous business questions into structured analytics problems and deliver insights that drive strategic decisions and operational improvements. Mentor and Lead Data Science Best Practices: Guide data scientists and analysts by promoting code quality, model validation, reproducibility, and responsible AI practices including performance monitoring, bias mitigation, and stakeholder education. Qualifications & Skills
5+ years as a Data Scientist with subject matter expertise in retail, with experience in customer segmentation, performance forecasting, and business optimization. Business Acumen: Ability to translate complex analytical insights into actionable strategies; proven track record of partnering with cross-functional teams to drive revenue outcomes. Retail Expertise: Experience developing and optimizing retail strategies through advanced analytics across brick-and-mortar and ecommerce channels. Data Visualization & Dashboarding: Proficient in developing intuitive dashboards and visual analytics to enable self-service insights and support data-driven decisions. Advanced Statistical Modeling: 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: Proficiency in designing and analyzing experiments, including A/B testing and geo-lift studies. Python Proficiency: Expert-level skills in Python for building scalable, production-ready models using libraries such as pandas, scikit-learn, statsmodels, and PyMC. SQL Expertise: Expert-level SQL skills for querying and manipulating large-scale datasets and building automated data pipelines. Big Data & Cloud Proficiency: Experience with Google Cloud Platform, Snowflake, BigQuery, and Spark for handling large-scale retail datasets. Education
Bachelor’s degree in Mathematics, Economics, Data Science, Computer Science, Operations Research, or related field, and/or equivalent work experience. Master of Science or PhD Additional Information
This role is located in Orlando, FL. Benefits and Perks: Disney offers a rewards package to help you live your best life, including health and savings benefits, educational opportunities, and other special extras. Learn more about our benefits and perks at Disney Careers.
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About The Role & Team: At Disney Consumer Products, we inspire imagination around the world and are committed to creating happiness for families and fans by bringing captivating, inspiring, and inclusive products into their daily lives. Our team brings brands and franchises into the lives of families through products and experiences found worldwide, such as the Disney Store e-commerce platform, Disney Parks, retailers, and Disney Store locations. The Merchandise Business Insight and Analytics (MBIA) team supports the full retail lifecycle by providing analytics, reporting, and insights that empower data-informed decision-making for stakeholders across Category and Location Planning, Product Development, Merchandising, and Retail Operations. We are seeking a
Sr. Data Scientist
to support and drive advanced analytics and data science initiatives for brick-and-mortar and ecommerce retail across Disney Experiences. This role focuses on developing and enhancing machine learning models and data-driven solutions to optimize customer segmentation, assortment rationalization, promotion optimization, and performance forecasting. The ideal candidate will have deep expertise in statistical modeling, machine learning, and retail strategy, enabling data-informed decisions that enhance guest experience and drive revenue growth across digital and physical retail environments. This role will report to the Sr. Manager, Data Science. What you will do
Lead End-to-End Model Development: Design, develop, and deploy advanced statistical and machine learning models (e.g., regression, classification, clustering, time series forecasting) to solve complex retail problems including customer segmentation, promotion optimization, and demand forecasting. Drive Scalable Data Solutions: Architect and implement scalable data pipelines and model workflows using Python, SQL, and cloud platforms (e.g., Google Cloud Platform, Snowflake) to support continuous data integration and model retraining across large-scale retail datasets. Develop Visual Analytics Tools: Build dynamic dashboards and self-service analytics solutions using Tableau, Looker, or similar platforms to monitor key business metrics, track model performance, and deliver actionable insights to cross-functional partners. Partner with Business & Technical Stakeholders: Collaborate with product, merchandising, marketing, and technology teams to translate ambiguous business questions into structured analytics problems and deliver insights that drive strategic decisions and operational improvements. Mentor and Lead Data Science Best Practices: Guide data scientists and analysts by promoting code quality, model validation, reproducibility, and responsible AI practices including performance monitoring, bias mitigation, and stakeholder education. Qualifications & Skills
5+ years as a Data Scientist with subject matter expertise in retail, with experience in customer segmentation, performance forecasting, and business optimization. Business Acumen: Ability to translate complex analytical insights into actionable strategies; proven track record of partnering with cross-functional teams to drive revenue outcomes. Retail Expertise: Experience developing and optimizing retail strategies through advanced analytics across brick-and-mortar and ecommerce channels. Data Visualization & Dashboarding: Proficient in developing intuitive dashboards and visual analytics to enable self-service insights and support data-driven decisions. Advanced Statistical Modeling: 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: Proficiency in designing and analyzing experiments, including A/B testing and geo-lift studies. Python Proficiency: Expert-level skills in Python for building scalable, production-ready models using libraries such as pandas, scikit-learn, statsmodels, and PyMC. SQL Expertise: Expert-level SQL skills for querying and manipulating large-scale datasets and building automated data pipelines. Big Data & Cloud Proficiency: Experience with Google Cloud Platform, Snowflake, BigQuery, and Spark for handling large-scale retail datasets. Education
Bachelor’s degree in Mathematics, Economics, Data Science, Computer Science, Operations Research, or related field, and/or equivalent work experience. Master of Science or PhD Additional Information
This role is located in Orlando, FL. Benefits and Perks: Disney offers a rewards package to help you live your best life, including health and savings benefits, educational opportunities, and other special extras. Learn more about our benefits and perks at Disney Careers.
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