Define and structure ambiguous supply chain problems into clear frameworks for decision-making
Synthesize insights into compelling narratives for executive audiences
Design quantitative models that evaluate trade-offs between cost, service, risk, and sustainability
Develop and compare scenarios, highlighting sensitivities, uncertainties, and financial implications
Establish standards for model documentation, validation, and version control
Own, maintain, and continuously enhance strategic planning models
Partner across various teams to maintain a strong pulse on customer needs
Drive clarity across cross-functional teams regarding constraints, assumptions, and strategic implications
Mentor and coach data scientists and analysts in structured problem solving

PhD or MS in Operations Research, Industrial Engineering, Applied Math, Physics, Computer Science or related quantitative field
5+ years’ experience applying quantitative modeling to large-scale supply chain or operational problems at scale
Demonstrated proficiency in Python programming and advanced SQL for data preparation, modeling and exploratory analysis
Experience working with mathematical optimization libraries or solvers (e.g. Gurobi)
Strong systems thinking skills and ability to reason from first principles
Proven track record communicating analytical insights to senior or executive audiences
Ability to operate independently in highly ambiguous, strategic environments
Demonstrated experience influencing cross-functional stakeholders
Experience framing or informing enterprise-level supply chain or capital decisions
Experience leading the design of modeling frameworks, analytical standards, or multi-scenario planning processes

Lead Data Scientist – Supply Chain Network Planning and Design, Operations Research, Optimization, Python

Key skills