Responsibilities

• Design and implement advanced optimization models supporting inventory allocation, transportation routing, and warehouse network planning.
• Develop scalable network modeling frameworks to evaluate distribution center locations, capacity planning scenarios, and cost-to-serve analyses.
• Utilize linear programming, mixed-integer programming, and heuristic algorithms to address large-scale and complex supply chain optimization problems.
• Analyze historical and real-time data to identify patterns, improve forecasting accuracy, and inform strategic initiatives.
• Collaborate cross-functionally with Supply Chain, Finance, and IT teams to integrate optimization solutions into enterprise processes and systems.
• Build simulation models to validate scenarios, assess trade-offs, and measure impacts on service levels, inventory, and cost.
• Translate technical insights and analytical findings into clear, compelling visualizations and presentations for executive stakeholders.

Qualifications

• BS/BA in Data Science, Operations Research, Industrial Engineering, or related field required; MS preferred.
• 5+ years of experience in data science, optimization, or operations research roles—ideally within supply chain or logistics environments.
• Strong proficiency in Python, SQL, and optimization libraries/tools such as Pyomo, Gurobi, and CPLEX.
• Expertise in network modeling, linear and mixed-integer programming, simulation techniques, and applied operations research.
• Familiarity with Snowflake and modern cloud-based data platforms.
• Exceptional analytical, quantitative, and problem-solving skills.
• Ability to translate complex models into practical, actionable business strategies with measurable impact.

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