Data Scientist II, Enterprise Data Science and AI

About the Role

The Enterprise Data Science and AI team at Gap Inc. is seeking a talented data scientist to work in the P2M space and help us drive growth, optimize inventory, and enhance operational excellence across all Gap Inc. brands. The team’s focus is on developing and deploying predictive and prescriptive analytics capabilities across different domains, including merchandising, inventory management, demand forecasting, and localization, in partnership with GapTech, Product Management, and business partners across our brands.

What You'll Do

• Design and execute controlled experiments or causal inference studies (e.g., A/B tests, quasi-experiments) to measure the true incremental impact of product or operational initiatives

• Drive causal insights behind core KPIs through robust statistical methods, and design experiments beyond A/B testing (e.g., multi-armed bandits, sequential tests, quasi-experiments)

• Develop and implement data-driven models to improve inventory availability and productivity

• Collaborate with data engineering teams to ensure data accessibility, integrity, and scalability for modeling and experimentation purposes

• Build the foundation for experimentation at scale by developing shared frameworks, tools, and documentation that standardize methodologies and establish robust standards for experimental integrity

• Communicate meaningful, actionable insights from large data and metadata sources to stakeholders to drive strategic adoption of data science models

• Explore cutting-edge intersections of generative AI and causal inference, developing LLM-driven prototypes that demonstrate new analytical and experimental capabilities

Who You Are

• Proven experience in applied experimentation, causal inference, statistical modeling, machine learning, operations research, or inventory theory with a track record of driving measurable business impact

• Hands-on experience developing and deploying end-to-end models in cloud-based environments such as Azure or GCP

• Expertise in working with large-scale datasets across distributed systems and data pipelines

• Strong proficiency in Python, SQL, and Spark (or similar frameworks) for data manipulation, modeling, and analysis

• Exceptional problem-solving ability, with a talent for translating complex data into clear, actionable business insights

• Effective communicator and stakeholder partner, capable of conveying technical concepts to non-technical audiences and building trusted, cross-functional relationships

• Skilled collaborator with experience influencing product and analytics roadmaps through data driven recommendations

• Bachelor’s or advanced degree in Data Science, Operations Research, Statistics, Mathematics, Computer Science, Industrial Engineering, or a related field

• Domain experience in retail, inventory management, or supply chain analytics strongly preferred