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.

 

 

Experiences/Education - Required
o Bachelor's degree in Operations Research, Industrial Engineering, Applied Mathematics, or a related quantitative discipline.
o 7+ years of practical experience applying operations research and industrial engineering techniques to solve business or engineering problems.
o Proficiency with optimization solvers (e.g., CPLEX, Gurobi, Pyomo+GLPK), simulation tools (e.g., AnyLogic, SimPy), and programming languages such as Python.
o Strong analytical and critical thinking skills; attention to detail and a passion for problem-solving.
o Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
o Collaborative team player with strong interpersonal skills.
o Curious, adaptable, and eager to continuously learn and apply new methods.
o Results-oriented and proactive in driving projects to completion.

Experiences/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. 

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