[Hiring] Supply Chain Network Modeler @Cencora

Role Description

Under general supervision of the Supply Chain Modeling & Optimization Director, the Supply Chain Network Modeler is responsible for developing, maintaining, and applying network models that transform complex supply chain data into actionable insights to support strategic and operational decision making.

This role works collaboratively with cross functional stakeholders and remote teams to:

• Identify modeling use cases
• Translate business questions into quantitative network scenarios
• Evaluate tradeoffs across cost, service, capacity, risk, and growth

The Network Modeler documents assumptions, validates data inputs, and communicates findings through interactive dashboards, visualizations, and structured storytelling to enable informed decisions.

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.

Qualifications

• 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.

Requirements

• Team oriented and highly collaborative working style.
• Strong analytical, conceptual, and problem solving skills.
• Ability to communicate effectively—both verbally and in writing—with technical and non‑technical stakeholders.
• Strong presentation and storytelling skills, with the ability to explain complex modeling outcomes clearly and persuasively.
• Strong organizational skills and attention to detail.
• Ability to manage multiple tasks and prioritize effectively in a dynamic environment.
• Demonstrates sound judgment and discretion when working with sensitive or complex information.
• Comfortable working in a remote, cross functional, multidisciplinary environment.
• Growth mindset with a strong interest in solving business challenges and continuously improving modeling capabilities.

Benefits

• Benefit offerings outside the US may vary by country and will be aligned to local market practice.
• The eligibility and effective date may differ for some benefits and for team members covered under collective bargaining agreements.