Operational Research Engineer

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Our Optical Communications segment has recently evolved from being a manufacturer of optical fiber and cable, hardware and equipment to being a comprehensive provider of industry-leading optical solutions across the broader communications industry. This segment is classified into two main product groupings – carrier network and enterprise network. The carrier network product group consists primarily of products and solutions for optical-based communications infrastructure for services such as video, data and voice communications.

The enterprise network product group consists primarily of optical-based communication networks sold to businesses, governments and individuals for their own use.

The division operations research engineer is focused on designing, developing, and deploying mathematical optimization, simulation, and advanced analytics solutions that address strategic business operations across planning, production, fulfillment, inventory, and operations.

• Collaborate with supply chain specialists, planners, operations teams, and engineers to define optimization problems and translate business needs into objective functions and mathematical constraints.
• Specify and gather data requirements, working with data scientists and engineers to pre-process data.
• Lead and Partner with corporate resources to architect and oversee the development of operations research solutions, including linear/mixed-integer optimization, network design, stochastic modeling, simulation, and scenario analysis.
• Participate in the design, development, and implementation of large-scale optimization models (LP, NLP, MILP) for manufacturing and scheduling challenges.
• Formulate and enhance model predictive control (MPC) applications.
• Develop optimization solutions using tools like Gurobi, Pyomo, AMPL, MATLAB, and other relevant platforms.
• Communicate complex models and insights to both technical and non-technical audiences, emphasizing business impact and risk/benefit trade-offs.
• Oversee the lifecycle of OR projects from scoping and modeling to validation, deployment, and impact measurement.
• Maintain rigorous documentation, version control, and governance for all models and analytical solutions.
• Develop and track KPIs for OR initiatives; ensure solutions deliver measurable improvements in operational cost, service level, efficiency, and revenue generation.
• Support expansion into next-generation analytics, automation, and operational resilience.
• Partner with a diverse team of OR professionals, simulation experts, and analytics modelers at both the corporate and plant levels.
• Foster a culture of critical thinking, knowledge sharing, and continuous improvement in advanced modeling techniques.

• Master’s/Bachelor’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Data Science, or related quantitative discipline.
• Minimum of 2-3 years of experience in numerical optimization or operations research roles in industry; additional academic experience is a bonus.
• Knowledge of operations research techniques, including mathematical programming (linear, mixed-integer, nonlinear), advanced simulation (discrete-event, Monte Carlo), stochastic modeling, and scenario analysis.
• Proficiency in analytics programming languages and tools such as Python (puLP, Pyomo, ortools), R, CPLEX, Gurobi, Any Logic, AMPL,…