Sr Applied Scientist - Allocation Optimization - Remote

Cystems Logic Inc; San Jose (CA); Hybrid; USD 165,312,000 - 247,968,000; Full time

Job summary

Cystems Logic Inc. in Irvine, CA seeks a Sr Applied Scientist to lead allocation optimization across regional stores. This 9-month contract role combines hands-on optimization work with model extension to new regions and business rules, plus retraining as stores come online.

The ideal candidate has strong mathematical optimization skills, Python with PuLP/OR-Tools, and experience with retail inventory logic and cloud tools like SageMaker and Lambda. Remote work is acceptable.

Qualifications

• Mathematical optimization via LP/constraint satisfaction/multi-objective
• Python with PuLP/OR-Tools; Gurobi familiarity a plus
• Retail inventory allocation and replenishment logic
• SageMaker, Lambda integration
• Comfortable in a federated data architecture (central model code, regional data)

Responsibilities

• Hands-on mathematical optimization for regional store allocation
• Extend constraint-based, multi-objective allocation framework to new regional store configurations
• Adapt models to regional business rules (store capacity, presentation minimums, lead times, clearance logic)
• Model retraining and tuning per region as stores come online
• Support explainability outputs for regional business teams

Skills

Mathematical optimization

Python programming

Retail allocation

Multi-objective optimization

Constraint programming

Federated data architectures

Tools

PuLP

OR-Tools

Gurobi

SageMaker

Lambda

Job description

Sr Applied Scientist - Allocation Optimization - Remote

• Contract

Hi,

Job Title: Sr Applied Scientist - Allocation Optimization

Location: Irvine, CA and remote acceptable too

Duration: 9 months Contract

We have below longterm job opening.

Availability:

Expected rate all inc on c2c /1099 :

Scope:

Hands-on mathematical optimization for regional store allocation

Extend existing constraint-based, multi-objective allocation framework to new regional store configurations

Adapt models to regional business rules (store capacity, presentation minimums, lead times, clearance logic)

Model retraining and tuning per region as stores come online

Support explainability outputs for regional business teams

Required:

Mathematical optimization (linear programming, constraint satisfaction, multi-objective)

Python (PuLP, OR-Tools; Gurobi familiarity a plus)

Retail inventory allocation and replenishment logic

SageMaker, Lambda integration

Comfortable in a federated data architecture (central model code, regional data)

Preferred:

Operations research background

Experience scaling optimization models across geographies

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