Optimization Specialist S P A Enterprise

3.0 - 7.0 years

0 Lacs

telangana

On-site

As an Optimization Specialist, you will be responsible for building and scaling mathematical models and process optimization. Your role will involve designing and implementing optimization models such as LP, MIP, and MILP for real-world scheduling, routing, and planning scenarios. Additionally, you will be expected to construct simulation models to evaluate performance under uncertainty, collaborate with cross-functional teams to refine problem definitions, and translate them into quantitative models. You will work closely with data scientists, software engineers, and business analysts to drive predictive optimization workflows using AI/ML algorithms for forecasting, clustering, and classification. Conducting what-if analyses and sensitivity testing to support decision-making will be a crucial part of your responsibilities. Furthermore, you will support research and pilot initiatives involving Quantum-Inspired Optimization (QUBO, hybrid models) and present findings and model performance to stakeholders through clear and concise visualizations and documentation. To excel in this role, you must possess a strong knowledge of Linear Programming (LP), Mixed Integer Programming (MIP/MILP), Constraint Programming, and have experience formulating and solving large-scale combinatorial problems. Hands-on experience with Optimization libraries like Pyomo, PuLP, and solvers such as CPLEX, Gurobi, GLPK, or CBC will be beneficial. Proficiency in programming languages like Python, R, or MATLAB is essential, along with simulation expertise in tools like SimPy, AnyLogic, Arena, or equivalent for discrete-event or agent-based simulation. Your educational background should include a PhD in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a related field. Additionally, applied machine learning knowledge including forecasting models, clustering, and model evaluation metrics (e.g., MAPE, RMSE) will be advantageous. Strong communication and documentation skills are necessary to effectively present models and insights to non-technical audiences.,

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