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.
Job Requirements
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.