The Enterprise Data Science and AI team at Gap Inc. is seeking a talented data scientist to help drive growth, optimize inventory, and enhance operational excellence across all Gap Inc. brands
Requirements
- Proven experience in applied experimentation, causal inference, statistical modeling, machine learning, operations research, or inventory theory
- 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
- Experience with generative AI and causal inference
- Experience with cloud-based environments such as Azure or GCP
- Experience with large-scale datasets and distributed systems
Responsibilities
- 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
Other
- Bachelors 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
- 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
- Exceptional problem-solving ability, with a talent for translating complex data into clear, actionable business insights
