Manager, Global Network Design & Optimization
About The Position
The Manager, Global Network Design & Optimization leverages advanced predictive modeling, mathematical optimization, machine learning, and quantitative analysis to solve complex strategic supply chain network challenges. The role develops data-driven solutions that improve service, cost, capacity planning, operational reach, and scalable growth through targeted investment. The position leads complex cross-functional analytics work, influences stakeholders through strategic recommendations, and advances modeling capabilities for long-range supply chain planning. This role contributes to the strategic direction of the supply chain by applying technical expertise, business insight, and forecasting discipline to network design and optimization decisions. This is a Hybrid position requiring 3 days per week onsite at either the Chicago, IL or Lake Forest, IL offices.
Requirements
- Bachelor’s degree in supply chain, Logistics, Industrial Engineering, Operations Research, Applied Statistics, Mathematics or a related quantitative field.
- 5+ years in applied quantitative fields influencing optimization of supply chain network design, operations planning, inventory planning, transportation, and/or other complex operational systems
- Knowledge of supply chain optimization concepts and mathematical modeling, including applied experience using supply chain optimization software such as Coupa Supply Chain Modeler, Optilogic Cosmic Frog, AnyLogistix, or related tools.
- Experience applying data science and advanced statistical methods to develop, validate, and apply predictive models that inform strategic business decisions under uncertainty.
- Experience leading the full lifecycle of complex analytics and modeling initiatives from problem scoping through business recommendation.
- Experience communicating quantitative concepts, modeling outcomes, and strategic recommendations effectively with technical partners, cross-functional stakeholders, and senior leadership.
Responsibilities
- Apply mathematical optimization, predictive modeling, machine learning, and other quantitative techniques to analyze, predict, and optimize complex logistics architectures, flows, and processes.
- Develop modeling approaches, analytical capabilities, and data sources to improve distribution network design, capacity planning, and long-range projections using tools such as Snowflake, Databricks, Python, R, and Gurobi.
- Lead complex cross-functional projects by setting direction for how supply chain network problems are structured, analyzed, and solved while aligning technical and business partners around long-range strategic recommendations.
- Translate complex analyses into strategic recommendations for senior leadership to support alignment on supply chain priorities, capacity decisions, operational investments, and service and cost improvement opportunities.
- Advance team modeling capabilities by identifying new methodologies, technologies, analytical approaches, and external partner capabilities that support current industry practices and future supply chain needs.
- Mentor team members by elevating analytical capability, promoting modeling best practices, and supporting consistent delivery of high-quality quantitative insights.
Benefits
- Medical, dental, vision, and life insurance plans with coverage starting on day one of employment
- 6 free sessions each year with a licensed therapist to support your emotional wellbeing.
- 18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date)
- 6 company holidays per year.
- 6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required.
- Employee discounts
- Tuition reimbursement
- Student loan refinancing
- Free access to financial counseling, education, and tools.
- Maternity support programs
- Nursing benefits
- Up to 14 weeks paid leave for birth parents
- Up to 4 weeks paid leave for non-birth parents.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
