Description

Build and maintain mathematical optimization models for logistics and supply chain operations, ensuring mathematical accuracy and business defensibility.

This role is on-site.

Responsibilities

• Encode business rules, contract parameters, and operational constraints into optimization models using solvers like CPLEX and OR-Tools.
• Validate input data and model outputs through regression testing, NULL checks, and anomaly detection before production runs.
• Monitor cloud pipeline health, audit logs, and ingestion failures, triaging platform issues with clear diagnostics.
• Perform scenario and sensitivity analysis to document trade-offs and provide business recommendations.
• Mentor junior team members on coding standards, documentation discipline, and best practices.

Required Skills

• 3–8+ years of experience in Data Science or Operations Research.
• Hands-on experience with optimization solvers (CPLEX, OR-Tools).
• Proficiency in Python for modeling, data validation, automation scripting, and production-quality coding.
• Strong SQL skills for data querying, pipeline monitoring, and audit log review.
• Experience with cloud platforms (AWS or equivalent).
• Strong documentation and stakeholder communication skills.

Preferred Skills

• Pipeline orchestration tools such as Dataiku or Airflow.
• Containerization with Docker and Kubernetes.
• REST API development using FastAPI.

Key Skills

Education

Bachelor's degree