Data Scientist - Operations Research

Lead production scheduling automation and optimization efforts using operations research methods, simulations, and data analysis. Deliver actionable optimization and inventory-management solutions by building algorithms and collaborating with cross-functional teams.

• Develop mathematical models and algorithms for optimization problems
• Implement optimization solutions using Python
• Build and run simulation models to evaluate scheduling strategies
• Perform exploratory data analysis and apply statistical and machine learning techniques
• Provide operations research expertise for supply chain projects including inventory management and replenishment planning

The role develops mathematical models and algorithms for optimization problems (linear programming, integer programming, mixed-integer programming, and constraint programming) and implements solutions in Python. It also uses exploratory data analysis and statistical/machine learning techniques, plus simulation models, to evaluate and improve scheduling and supply chain strategies including multi-echelon probabilistic inventory optimization.

The ideal candidate is a mid-level data scientist with 1-3 years of operations research project experience and strong Python proficiency. They have built optimization models using linear programming, integer programming, mixed-integer programming, and constraint programming, and they apply simulation and exploratory data analysis to improve supply chain and manufacturing performance.