Duration: 12 months, possibility of extension
Pay: $63 hourly
Job Description
Key Responsibilities
Develop and implement mathematical programming, simulation models, and cost models (e.g., linear and mixed-integer programming, discrete-event simulation) to address real-world business challenges.
Analyze process flows, resource allocation, production planning, and logistics scenarios, recommending evidence-based improvements.
Collect, clean, and analyze operational data; translate findings into model parameters and actionable insights.
Collaborate with cross-functional teams to frame business problems, gather requirements, and present results to technical and non-technical audiences.
Document models, methodologies, and results; support knowledge sharing and team best practices.
Assist in deploying optimization, simulation, and cost modeling tools into production using modern software and platforms.
Experience/Education – Required
Bachelor s degree in Operations Research, Industrial Engineering, Applied Mathematics, or a related quantitative discipline.
7 years of practical experience applying operations research and industrial engineering techniques to solve business or engineering problems.
Proficiency with optimization solvers (e.g., CPLEX, Gurobi, Pyomo GLPK), simulation tools (e.g., AnyLogic, SimPy), and programming languages such as Python.
Strong analytical and critical thinking skills with attention to detail and a passion for problem-solving.
Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
Collaborative team player with strong interpersonal skills.
Curious, adaptable, and eager to continuously learn and apply new methods.
Results-oriented and proactive in driving projects to completion.
Experience/Education – Desired
Master s degree preferred.
Experience with data preparation, workflow automation, and visualization is a plus.
Exposure to manufacturing, supply chain, or commercial analytics preferred.