Description

Apply operations research techniques to solve complex logistical and scheduling problems.

Responsibilities

• Gather requirements to determine the applicability of operations research solutions.
• Formulate objective functions and constraints for mathematical models.
• Perform data extraction, cleaning, and analysis on structured datasets.
• Develop and implement large scale optimization models using linear programming, mixed integer programming, and heuristics.
• Solve problems related to staff scheduling, vehicle movement, and route optimization.

Required Skills

• Master’s or PhD in a quantitative discipline such as Operations Research, Engineering, Computer Science, Applied Mathematics, or Statistics.
• Experience with Python for optimization solutioning.
• Proficiency in at least one Object Oriented programming language, specifically C++ or Java.
• Strong SQL knowledge for querying and analyzing structured data.
• Deep knowledge in at least one OR area, including optimization, simulation, or statistics.
• Practical experience in logical analysis and problem identification.

Preferred Skills

• 2+ years of experience in a technical professional environment.
• Experience building enterprise level optimization applications.
• Hands-on with Gurobi, MATLAB, or IBM CPLEX.

Key Skills

Education

Bachelor's degree in Computer Science