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Responsibilities:
- Develop and extend constraint-based, multi-objective allocation frameworks for regional stores.
- Adapt optimization models to incorporate regional business rules (e.g., store capacity, lead times).
- Support model retraining and tuning per region as stores come online.
Requirements:
- Expertise in mathematical optimization (linear programming, constraint satisfaction, multi-objective).
- Proficiency in Python with PuLP, OR-Tools, or Gurobi, and experience in retail inventory allocation.
- Comfort with federated data architectures and SageMaker integration.
About the Role:
- 9-month contract position with remote flexibility from Irvine, CA or elsewhere in the US.
- Hands-on focus on regional store allocation optimization and explainability outputs.
- Collaboration with regional business teams to adapt core models.
The company is a technology giant specializing in internet-related services and products. As a large global organization, it fosters a culture of innovation and collaboration, with a focus on data-driven decision-making.