Manager Data Science
About the role
The Manager II, Modeling & Capacity Planning, is responsible for leading advanced analytical modeling and capacity planning efforts to support end-to-end supply chain performance. This role leverages quantitative modeling, machine learning algorithms, and AI techniques to translate complex operational data into actionable insights that optimize material flows, capacity utilization, network efficiency, service levels, and cost.
Responsibilities
Network Modeling & Tool Development - Develop custom optimization tools in Python using Gurobi to solve complex problems in transportation routing, inventory optimization, origin destination pairings. Design and execute scenario analysis to evaluate trade-offs related to demand variability, labor and asset capacity, network changes, and service-level commitments. Provide recommendations that balance cost, service, and operational risk.
Applied Machine Learning Techniques & Advanced Analytics - Implement ML and AI techniques in supply chain use cases: predictive models, clustering techniques, computer vision, deep learning, and forecasting algorithms.
Strategic Planning & Roadmap Development - Support the creation of strategic roadmaps for network growth, modernization, and optimization initiatives. Develop standardized evaluation models for expansion, network redesigns, and transportation optimization projects. Conduct scenario planning and forward-looking analyses to guide investment and operational decisions.
Capacity Planning Models - Develop, maintain, and enhance capacity planning models that predict volume flows, resource requirements, and operational constraints across the supply chain network.
Operational Insights & Optimization - Analyze supply chain performance trends to identify bottlenecks, inefficiencies, and improvement opportunities. Translate insights into actionable recommendations aligned with business objectives.
Cross-Functional Collaboration - Partner with Operations, Transportation, Warehousing, Inventory Planning, Finance, and Technology teams to align modeling assumptions, KPIs, and planning outputs with real-world constraints and strategic priorities.
Performance Measurement & KPIs - Define, monitor, and refine capacity and planning KPIs. Develop reporting and visualization tools to communicate performance, risks, and opportunities to leadership.
Testing & Validation - Design and execute stress tests, simulations, and what-if analyses to validate models and quantify the impact of planning decisions.
People Leadership & Mentorship - Lead, coach, and develop analysts and planners, ensuring consistent modeling standards, analytical rigor, and timely delivery of insights.
Technology & Data Partnership - Collaborate with IT and data teams to ensure data integrity, improve data pipelines, and support system enhancements that enable scalable modeling and planning solutions.
Requirements
- Bachelor's degree in industrial engineering, Operations Research, Supply Chain Management, Applied Mathematics, Statistics, Computer Science, or a related quantitative field required.
- Master's Degree preferred (e.g., Supply Chain, Analytics, Operations Research, Computer Science, Statistics).
- 7+ years of progressive experience in optimization, network design, supply chain analytics, capacity planning, or forecasting.
- 3+ years of experience leading advanced quantitative models or decision-support tools.