Co-op: Supply Chain Optimization (Fall 2026)
Logistics, Sales & Operations · Supply Chain & Transport · Logistics Management
In short
Support the Demand and Inventory Planning team by building and enhancing supply chain data analytics tools. This co-op role offers the opportunity to apply academic knowledge in a professional environment, work on projects, and develop skills in Power BI, Python/R, and supply chain modeling.
Responsibilities
- Leverage Power BI, Python / R and advanced analytics tools and techniques to visualize demand and inventory data.
- Develop and improve data structures to enhance data accessibility, quality and efficiency.
- Improve existing supply chain optimization models (total cost, forecast parameters) in Python / R.
- Identify, analyze and interpret trends or patterns in complex data sets.
- Prepare brief written summaries of learning experiences and project updates.
- Present project findings to peers, management, and senior leaders.
Requirements
- Currently enrolled and pursuing a degree in Mathematics / Statistics, Industrial Engineering, Data Analytics, or a related field.
- Completed 30 semester hours prior to the start of the internship.
- Minimum cumulative grade point average of 2.75.
- Proficient in Microsoft Office Applications (Excel, Access, Word, and PowerPoint).
- Interest in pursuing a professional career in Logistics / Supply Chain Management, Data Science, or a related field.
- Co-ops may work up to 40 hours per week and are not enrolled in academic courses.
Desired Qualifications
- Master’s degree is a plus.
- Experience with visualization tools (specifically Power BI).
- Experience with programming (R/Python).
- Experience with supply chain modeling.
- Knowledge of supply chain concepts like economic order quantity, safety stock, forecast errors and bias, and inventory health.
Benefits
- Hourly range: $17.00 - $46.00.
- Housing assistance, when applicable.
- Countless career opportunities / internal mobility across our global organization.
- Training and personal development.
#Supply Chain#Data Analytics#Logistics#Planning