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Niche OR/AI role requiring specialized optimization skills, reducing qualified applicant density.
Specialized operations research and optimization expertise limits cross-industry transferability.
Explicit 5–10 years, PhD/Master and specialized OR/ML certifications make shortlisting stringent.
Develop and implement advanced optimization models to enhance operational efficiency and cost-effectiveness across logistics, supply chain, manufacturing, and business processes.
Design and apply AI and machine learning techniques, including combinatorial optimization and hybrid models, to support business decision-making and optimize EV fleet operations.
Collaborate cross-functionally with business, data science, IT, and finance teams to align models with strategic objectives and communicate insights to senior leadership.
Ph.D. or Master’s degree 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 & OR (CPLEX/Gurobi) and advanced AI & ML certifications from recognized providers (e.g., Google, AWS, Microsoft).
Not explicitly mentioned in the JD: Notice period or strict location/onsite requirements.
Experienced in integrating mathematical optimization with advanced AI/ML techniques to solve complex business problems and drive process automation.
Demonstrated ability to design scalable, data-driven decision support systems and contribute to strategic planning in dynamic, cross-functional environments.
Strong communication skills for translating technical models into actionable insights for executive leadership and ensuring regulatory compliance in AI governance.