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Niche OR skills but popular Data Scientist title and metro location create moderate applicant competition.
OR specialization limits transferability outside quantitative roles and supply chain contexts.
Specific solver and OR expertise required, but fresh graduates and internships accepted so filters are moderately strict.
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Formulate and implement optimization models for supply chain, inventory, production planning, and pricing problems using linear, integer, and mixed-integer programming.
Prototype and evaluate alternative optimization formulations and solution strategies, balancing optimality, robustness, and runtime performance.
Collaborate with delivery and engineering teams to integrate optimization models into end-to-end decision workflows and engage with customers to gather requirements and explain model trade-offs.
Bachelor’s or Master’s degree in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, or related quantitative field.
1-3 years of experience in optimization/operations research, including internships, academic projects, or industry experience; outstanding fresh graduates eligible.
Hands-on experience with at least one commercial/open-source solver (Gurobi, CPLEX, COIN-OR) and at least one programming language (preferably Python).
Strong foundations in linear algebra, probability, optimization theory, and algorithms with clear intuition for LP/MIP modeling.
Strong interest and demonstrated passion for Operations Research, supported by relevant coursework, theses, competitions, or open-source contributions.
Ability to reason from first principles, question assumptions, and iterate on optimization formulations effectively.
Experience or interest in working with real-world business data and operationalizing optimization solutions in a fast-paced environment.