Python MILP

We are seeking a skilled Operations Research Scientist / Optimization Specialist to design, develop, and implement advanced optimization models and scheduling algorithms that solve complex operational challenges. You will work closely with cross-functional teams to translate business problems into mathematical models, leveraging your expertise in Mixed Integer Linear Programming (MILP), production network design, and data analytics. Proficiency in Python and hands-on experience with optimization solvers are essential.
Key Responsibilities:
Design and develop optimization models (e.g., MILP, LP, heuristics) for supply chain, manufacturing, logistics, or resource allocation problems.
Implement advanced scheduling algorithms to improve operational efficiency and service levels.
Translate real-world business challenges into mathematical models and provide actionable insights.
Use Python and optimization libraries (e.g., Gurobi, CPLEX, Pyomo, PuLP) to build, test, and deploy scalable solutions.
Analyze large datasets to identify trends and validate model assumptions.
Collaborate with data scientists, engineers, and business stakeholders to integrate optimization models into decision-support systems.
Continuously evaluate and enhance model performance based on feedback and operational outcomes.
Document model design, assumptions, validation processes, and results clearly and effectively.