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About the role
Key responsibilities & impact- Own a hard, well-defined merchandising data science problem end-to-end, from business question through production system
- Define decision variables, recommendation logic, objectives, constraints, fallback behavior, and success criteria
- Determine whether to build an automated decision engine or a human decision-support system
- Select and implement optimization, heuristics, simulation, forecasting, causal/statistical inference, or hybrid approaches
- Build production systems integrated with merchandising, planning, and platform systems
- Establish methods and quality standards for Senior Data Scientists and engineers
- Define metrics and run experiments to validate improvements
- Create documentation, reusable components, and decision frameworks
- Identify the next important iteration of the problem
- Use AI-accelerated development tools while maintaining correctness and maintainability
- Communicate problems, tradeoffs, recommendations, and impact to engineering leads, merchants, and business stakeholders
Requirements
What you’ll need- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 5 years' experience in an analytics-related field; OR master's degree in one of these fields and 3 years' experience; OR 7 years' experience in an analytics or related field
- Track record of taking a hard, specific business question and shipping a system that measurably improved the answer
- Solid depth in optimization/decision methods and applied ML/forecasting/causal inference where relevant
- Experience with demand or elasticity estimation, long-horizon or seasonal forecasting, constrained planning/execution, assortment or allocation optimization, or competitive/price response modeling
- Experience in merchandising, retail, supply chain, or a comparable setting
- Ability to build systems for automated machine decisions and human decision support
- Ability to improve the work of others through review, mentorship, or reusable standards
- Judgment on optimality versus robust heuristics and automation versus human decision support
- Ability to communicate tradeoffs and recommendations clearly
- No people-management experience required
Benefits
Comp & perks- Incentive awards for performance
- Maternity and parental leave
- PTO
- Health benefits
- Compensation package