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Niche OR role but mid-level experience, metro location, and strong corporate brand increase competition moderately.
Specialized OR and algorithm skills are transferable across logistics, manufacturing, and supply chain but remain domain-specific.
Requires PhD/Master's, 5-10 years, OR algorithms, certifications, and domain deployment experience.
Design, develop, and implement optimization and simulation models to improve operational efficiency and reduce costs across ports, logistics, transportation, supply chain, manufacturing, and sourcing.
Leverage advanced mathematical, statistical, and AI techniques including linear programming, combinatorial optimization, and AI/ML methods to create scalable, data-driven decision support systems.
Collaborate with multiple stakeholders including business, IT, finance, and data science teams to integrate models into strategic and tactical decision-making and ensure AI governance and compliance.
Master’s or Ph.D. in Operations Research, Industrial Engineering, Statistics, Applied Mathematics, Computer Science, or related fields.
5-10 years of experience in developing and deploying operations research models in engineering, logistics, manufacturing, or supply chain domains.
Certification in optimization tools (e.g., CPLEX, Gurobi), advanced AI & ML (Google, AWS, Microsoft), and data science/statistical analysis.
Work Experience Required: 5-10 years; Notice Period: Not explicitly mentioned in the JD.
Experienced in applying advanced optimization algorithms and AI techniques to large-scale, real-world business problems, especially in logistics and supply chain domains.
Ability to translate complex mathematical models into actionable business insights and communicate effectively with C-level executives and cross-functional teams.
Demonstrated capacity to lead AI integration, model validation, and ensure regulatory compliance in an evolving technology and infrastructure environment.