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Strong employer brand and metro location but specialized OR skillset limits broad applicant pool.
OR, optimization, and digital-twin skills transfer across industries, though pharma compliance increases domain specificity.
Requires advanced quantitative degree plus specific OR solvers and simulation tool experience, enforcing strict filters.
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Design and implement operations research models and decision-support tools to solve complex clinical and commercial supply chain challenges.
Develop and deploy scalable Python-based analytical, optimization, and simulation applications supporting strategic and operational decision-making under uncertainty.
Collaborate cross-functionally to deliver data-driven solutions enhancing supply chain performance, resilience, and digital twin capabilities.
Advanced degree (MS or PhD preferred) in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Data Science, or related quantitative field.
Strong programming experience in Python for analytical application development.
Experience with operations research techniques and optimization solvers (e.g., Gurobi, CPLEX, OR-Tools).
Work Experience Required: Not explicitly mentioned in the JD.
Expertise in quantitative modeling combined with hands-on software engineering to build production-quality analytical software.
Experience with digital twin platforms or simulation tools (AnyLogic preferred) and understanding of enterprise data architecture.
Ability to work effectively in cross-functional teams with product, business, technology, and data engineering stakeholders.