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About the Role
Gap Inc. is seeking a Data Scientist to join their Product-to-Market (P2M) Data Science team. This team applies machine learning, optimization, and analytics to improve decisions across the P2M lifecycle, which encompasses product planning, inventory management, and pricing strategies. This is a hands-on role for an early-career professional with strong quantitative and programming fundamentals, eager to solve real-world retail problems at scale in a fast-paced, evolving environment.
Responsibilities
- Develop and test machine learning, optimization, and statistical models for retail P2M problems
- Analyze large datasets and develop analytical solutions using Python, SQL, and related technologies
- Write reliable, maintainable code and contribute to testing, documentation, and code management
- Evaluate model performance and support measurement of business impact using appropriate statistical methods
- Work with senior data scientists to troubleshoot, improve, and operationalize analytical solutions
- Collaborate with business, product, engineering, and data science partners to understand requirements and communicate analytical findings
Requirements
- Master’s degree in Operations Research, Operations Management, Industrial Engineering, Applied Mathematics/Statistics, Data Science, or a related quantitative field
- 2 to 3 years of experience in data science, machine learning, operations research, or applied analytics
- Experience working on retail, supply chain, pricing, inventory, merchandising, or related business problems
- Strong foundation in machine learning, statistics, and quantitative problem solving
- Hands-on proficiency in Python and SQL
- Self-motivated with demonstrated initiative and the ability to operate effectively in a fast-paced, evolving environment
- Strong analytical, communication, and collaboration skills
- Experience with mathematical optimization, including linear or mixed-integer programming, and tools such as Gurobi, Pyomo, OR-Tools, or equivalent
- Exposure to PySpark, Databricks, GCP, Git, or production data science environments
- Familiarity with experimentation or causal methods for measuring business impact
- Exposure to building AI agents or agentic workflows using large language models
Skills
- Python
- SQL
- Machine Learning
- Optimization
- Statistics
- Quantitative Problem Solving
- Mathematical Optimization
- Linear Programming
- Mixed-Integer Programming
- PySpark
- Databricks
- GCP
- Git
- Experimentation
- Causal Methods
- AI Agents
- Agentic Workflows
- Large Language Models
Experience Level
- 2 to 3 years of experience
- Early career
Education Level
- Master’s degree in Operations Research, Operations Management, Industrial Engineering, Applied Mathematics/Statistics, Data Science, or a related quantitative field
About the Company
- Gap Inc. is a company focused on Product-to-Market (P2M) strategies, encompassing decisions from product planning to customer delivery, including inventory management, and pricing.