Operations & Supply Chain Domain ExpertiseRole Overview
We are seeking a highly analytical Data Scientist to serve as a technical cornerstone within our Supply Chain organization. This role sits at the intersection of Mathematical Optimization, Statistics, and Software Engineering, focusing on uncovering hidden insights and driving data‑driven decision‑making. You will be responsible for designing and deploying innovative prescriptive analytics solutions that optimize our global operations at strategic, tactical, and operational levels.
Key Responsibilities
* Advanced Modeling: Develop and deploy complex mathematical programming models (MILP, NLP, etc.) to optimize long‑term supply chain and manufacturing processes.
* End‑to‑End Analytics: Perform statistical analysis on diverse healthcare datasets (structured and unstructured) to extract actionable business intelligence.
* Algorithmic Development: Design and implement custom computational solutions using high‑performance languages like Julia, Python, or Mosel.
* Cross‑Functional Collaboration: Partner with stakeholders across the organization to translate ambiguous business problems into rigorous technical requirements and scalable solutions.
* Tool Integration: Leverage industry‑leading solvers (Gurobi, CPLEX, BARON) to solve large‑scale resource allocation, scheduling, and inventory challenges.
Required Qualifications
* M.Sc. or Ph.D. in Operations Research, Industrial Engineering, Computer Science, Statistics, or a related quantitative field.
* Proven experience in mathematical programming and algorithm development for process optimization.
* Advanced coding skills in Python, Julia, or R, with hands‑on experience using optimization solvers.
* Solid understanding of supply chain fundamentals (planning, inventory management, scheduling) and manufacturing business processes.
* Working knowledge of machine learning (regression, clustering, neural networks) and experience handling large‑scale datasets.
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