AI Analyst, Supply Chain (On-site)

Sunset•Livonia, MI

7d•Onsite

About The Position

Mastronardi Produce, a leading greenhouse vegetable company, is seeking an AI Analyst-Supply Chain to join their Information Technology team at their corporate office in Livonia, Michigan. This role is responsible for designing, implementing, and supporting automation and AI-enabled solutions to modernize Supply Chain operations. The focus is on increasing efficiency, accuracy, and speed across supply planning, warehouse operations, and category management by applying automation, analytics, and AI to various systems including planning tools, warehouse management systems, ERP, and operational data. The position requires close collaboration with Supply Chain, DC operations, and Category Management teams to deliver production-ready solutions integrated with existing systems and built to support time-sensitive decisions in a fresh produce environment. The role emphasizes adherence to the company's PRIDE values: Passion, Respect, Innovation, Drive, and Excellence.

Requirements

Bachelor’s degree/Diploma in relevant field required
Minimum of 2 years of experience in AI with a specialization in Supply Chain
Experience working in supply chain, warehouse operations, supply planning, or category management — or in a technical role directly supporting these functions in a distribution, manufacturing, or fresh produce environment.
Working knowledge of supply chain operations across supply planning, warehouse, and category management — including demand forecasting, replenishment, inventory management, DC workflows, product performance analysis, and supplier or grower data.
Demonstrated experience translating business pain points into automation and AI solutions used in day-to-day operations.
Process mapping: experience documenting current-state workflows, identifying manual steps and inefficiencies, and defining requirements before building automation.
Testing and validation: disciplined approach to testing automation and AI solutions including functional testing, edge case validation, and user acceptance testing before supply chain teams rely on outputs.
Agentic AI awareness: understanding of AI agents and multi-step autonomous workflows — what they are, where they apply in supply chain operations, and how to evaluate or implement tools in this space as the technology matures.
Hands-on experience with AI tools in a business context — including Claude (Anthropic), Microsoft Copilot (M365), or equivalent — with the ability to design and refine prompts that produce reliable, consistent outputs; understanding of where AI adds value and where outputs require human review before use.
Microsoft Power Automate: designing and deploying automated workflows that connect systems, trigger actions based on supply chain events, route exceptions, and reduce manual handoffs across planning, warehouse, and category teams.
Power BI: building supply chain-facing dashboards, reports, and data models covering inventory, DC throughput, waste, planning performance, and category metrics; working knowledge of DAX and Power Query expected.
Python: scripting for data processing, transformation, and automation using common libraries (pandas, openpyxl, or equivalent).
SQL: ability to query, join, and filter data across relational databases in support of supply chain reporting, inventory analysis, and operational decision-making.
ERP Systems: experience working in or building automation around ERP platforms (Microsoft Dynamics NAV/365, SAP, or equivalent); understanding of supply chain data structures and integration points relevant to planning, warehouse, and procurement.
Microsoft Excel (advanced): strong working knowledge including Power Query and formula-based automation as a baseline for identifying and replacing manual supply chain processes.

Responsibilities

Translate supply chain objectives and operational pain points across planning, warehouse, and category management into practical, scalable automation and AI solutions.
Map and document current supply chain processes to identify inefficiencies, manual steps, and automation opportunities before designing solutions.
Design, build, and deploy automation and AI solutions across supply planning workflows including demand and replenishment planning, inventory positioning, exception management, and waste reduction.
Build automation and AI solutions that improve warehouse operations across distribution center workflows.
Support category management teams with automation and AI solutions that improve product performance visibility, assortment analysis, supplier data management, and reporting.
Apply AI to support data preparation, exception identification, forecast validation, waste flagging, and operational reporting across supply chain functions.
Test solutions thoroughly before deployment, including functional testing, edge case validation, and operational user acceptance testing to ensure outputs are accurate and reliable.
Identify opportunities to build reusable automation components that can be applied across multiple supply chain processes and locations.
Ensure AI outputs meet operational accuracy and data integrity requirements across WMS, ERP, planning, and TMS systems.
Define success metrics for each solution and track adoption, performance, and operational impact post-deployment.
Work closely with supply chain, DC, and category management users to gather feedback, drive adoption, and continuously improve solutions through ongoing enhancements and hands-on training.
Create and maintain clear documentation for all solutions, workflows, and operating procedures.
Ensure all solutions align with IT governance, security, and compliance standards.