Disney Consumer Products is 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 will focus on developing and enhancing machine learning models and data-driven solutions to optimize key areas such as customer segmentation, assortment rationalization, promotion optimization, and performance forecasting.
Requirements
- Advanced Statistical Modeling: Deep knowledge of predictive modeling techniques such as 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, geo-lift studies, and other causal frameworks to measure the impact of retail changes.
- Python Proficiency: Expert-level skills in Python, with demonstrated ability to build scalable, production-ready pricing and forecasting models using libraries such as pandas, scikit-learn, statsmodels, and PyMC.
- SQL Expertise: Expert-level skills in SQL for querying and manipulating large-scale retail and transactional datasets, with experience building automated data pipelines.
- Big Data & Cloud Proficiency: Hands-on experience working with large-scale data environments using platforms such as Google Cloud Platform (GCP), Snowflake, BigQuery, and Spark to ingest, process, and analyze complex retail datasets efficiently and at scale.
- Data Visualization & Dashboarding: Proficient in developing intuitive, impactful dashboards and visual analytics using tools (e.g., Tableau) to enable self-service insights, monitor key retail metrics, and support data-driven decision-making across stakeholders.
Responsibilities
- 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.
Other
- 5+ years as a Data Scientist with subject matter expertise in retail, with experience in areas including 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 such as Merchandising, Operations, Finance, and Marketing to drive revenue outcomes.
- Retail Expertise: Proven experience developing and optimizing retail strategies through advanced analytics, including customer segmentation, demand forecasting, promotional analysis, and performance measurement across both brick-and-mortar channels and ecommerce channels.
- Bachelor’s degree in Mathematics, Economics, Data Science, Computer Science, Operations Research, or a related field of study, and/or equivalent work experience.
- Master of Science or PhD
