Supply Chain Network Modeler

Responsibilities

• Develop, maintain, and enhance end-to-end supply chain network models covering facilities, flows, transportation, capacity, inventory, and service performance.
• Translate business problems into scenario‑based network analyses that evaluate cost to serve, service levels, capacity constraints, and investment alternatives.
• Partner with Supply Chain, Transportation, Finance, Engineering, and Operations teams to:
  • Scope modeling opportunities
  • Gather and validate inputs
  • Align scenarios and assumptions
  • Interpret and communicate results
• Support network optimization and simulation initiatives by building scalable models and reusable templates for recurring analyses.
• Create standardized dashboards and visualizations to communicate model inputs, outputs, and trade‑offs to technical and non‑technical audiences.
• Document modeling assumptions, methodologies, data sources, and limitations to ensure transparency, repeatability, and governance.
• Maintain and improve data models and datasets that support supply chain network analytics.
• Contribute to the development of modeling best practices, templates, and training materials to support the growth of internal “citizen modelers.”
• Stay current with emerging trends in network modeling, optimization, simulation, and advanced analytics.

Requirements

• Bachelor’s or Master’s degree in Industrial Engineering, Operations Research, Supply Chain, Data Analytics, Mathematics, Statistics, Computer Science, or a related field.
• Typically requires 3+ years of experience in supply chain analytics, network modeling, optimization, or related quantitative roles.
• Demonstrated experience applying analytical techniques to business problems and translating results into actionable recommendations.
• Supply chain industry or distribution network experience strongly preferred.
• Solid foundation in quantitative modeling, statistics, and optimization techniques.
• Hands‑on experience with supply chain network modeling or optimization tools (e.g., Llamasoft/Coupa, AnyLogistix, OptiLogic, or similar) preferred.
• Proficiency in data analysis and modeling languages such as Python, R, SQL, SAS, Databricks.
• Experience working with large datasets and integrating data from ERP, WMS, TMS, transportation, inventory, or forecasting systems.
• Familiarity with business intelligence and visualization tools (Power BI, Databricks, Tableau, Qlik, etc.).
• Understanding of cost to serve, transportation tradeoffs, capacity planning, and service optimization concepts.
• Experience building business cases and proposals that need to be presented in front of the leadership team for decision making.
• Understanding of trade offs between capex and opex.
• Lean, Six Sigma, or continuous improvement experience is a plus.