Sr Applied Scientist - Allocation Optimization

TL;DR

Sr Applied Scientist - Allocation Optimization (Mathematical Optimization/Python): Extending constraint-based, multi-objective allocation models for regional retail store configurations with an accent on capacity rules, presentation minimums, lead times, and clearance logic. Focus on retraining and tuning models across regions, integrating AWS services, and building explainability outputs for regional business teams.

Location: Remote work is acceptable within the United States; onsite work is available in Irvine, California.

Company

Technology services provider delivering software and data solutions for business clients.

What you will do

• Extend an existing constraint-based, multi-objective allocation framework for new regional store configurations.
• Adapt optimization models to regional rules covering store capacity, presentation minimums, lead times, and clearance logic.
• Retrain and tune models as stores come online in different regions.
• Integrate optimization workflows with SageMaker and Lambda.
• Produce explainability outputs for regional business teams.
• Work with centralized model code and region-specific data in a federated data architecture.

Requirements

• Hands-on experience with mathematical optimization, including linear programming, constraint satisfaction, and multi-objective optimization.
• Strong Python skills with PuLP or OR-Tools.
• Experience with retail inventory allocation and replenishment logic.
• Experience integrating models with SageMaker and Lambda.
• Comfort working in a federated data architecture.
• Must be able to work in the United States; remote work or onsite work in Irvine, California is acceptable.

Nice to have

• Familiarity with Gurobi.
• Operations research background.
• Experience scaling optimization models across multiple geographies.

Culture & Benefits

• Nine-month contract engagement.
• Work arrangement can be remote or onsite in Irvine, California.
• Opportunity to work on regional retail allocation and optimization systems.
• Information is handled confidentially in accordance with EEO guidelines.