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Ford is an American automaker founded in Dearborn in 1903 by Henry Ford, who introduced the moving assembly line and turned the car into a mass-market product. It is now organised into three businesses reported separately: Ford Blue for internal combustion vehicles, Model e for electric vehicles and software, and Ford Pro for commercial customers, which bundles vans and trucks with telematics, servicing and charging under multi-year contracts. Listed on the New York Stock Exchange and still partly controlled by the founding family through a special class of shares, its F-Series pickup has been the best selling vehicle in the United States for decades.

When applying for this position, please ensure you use your external-facing profile / resume to avoid screening rejection.

Job Description: Supply Chain Analyst - AI-Enabled Supply Continuity & Process Innovation

Position Overview

We are looking for a proactive Supply Chain Analyst who can navigate the tension between traditional supply assurance - supplier follow-up, delivery risk assessment, and expediting decisions - and the new frontier of AI-powered process innovation. This role is designed for someone who can partner with IT and Analytics teams to co-create intelligent automations while simultaneously building their own lightweight AI tools (using Microsoft Copilot and Office 365) to reduce manual effort, improve decision speed, and democratize AI capability across the supply chain function.

When applying for this position, please ensure you use your external-facing profile / resume to avoid screening rejection.

Key Responsibilities

  • Supplier Delivery Follow-Up & Line Risk Management - Own day-to-day follow-up with suppliers on delivery commitments; proactively identify at-risk orders using AI-generated alerts and predictive flags, and make real-time expediting decisions (air freight, alternate sourcing, buffer stock) to prevent line stoppages.
  • AI-Augmented Risk Assessment & Escalation - Leverage AI/ML-based scoring (powered by models built in collaboration with Analytics or prototyped via Copilot/Python) to quantify supplier risk across dimensions like lead time vulnerability, past reliability, and financial health, enabling prioritized escalation.
  • Data-Driven Expedite Decisioning - Use predictive scenario modeling and AI-generated recommendations to determine when expediting is truly necessary, balancing premium cost against production downtime risk, with clear reasoning documented for audit trails.
  • Cross-Functional Collaboration with IT & Analytics - Act as the supply chain subject matter expert embedded in cross-functional squads with IT and Data Analytics, translating manual workflows into technical requirements for automation, AI agents, and intelligent dashboards.
  • Microsoft Copilot & Office 365 Agentic Automation - Build and deploy Copilot-powered AI agents within Office 365 (Excel, PowerPoint, Outlook, Teams, Power Automate) to auto-generate weekly delivery status decks, draft supplier escalation emails, summarize meeting action items, and create workflow-based automations that eliminate repetitive tasks.
  • Democratized AI & Self-Sufficiency - Champion a "citizen developer" mindset: create reusable Copilot prompt libraries, pre-built Power Automate templates, and simple agentic workflows that enable non-technical colleagues to solve their own automation needs without dependency on IT.
  • Intelligent Process Optimization - Identify high-frequency, judgment-heavy processes (e.g., weekly risk reviews, expedite approval chains, delivery report generation) and redesign them as augmented or fully autonomous AI workflows in partnership with Analytics and IT.
  • GCP Data Wrangling & Dashboarding (Plus) - Utilize Google Cloud Platform tools (BigQuery for querying, Looker/Data Studio for visualization) to clean, merge, and visualize supplier performance data, enabling real-time risk dashboards that support proactive decision-making.
  • Analytics-Driven Insight Generation - Apply an "analytics eye" to surface underlying trends, anomalies, and early-warning signals from supply chain data - moving beyond descriptive reporting toward predictive and prescriptive insights that shape procurement strategy.
  • Continuous AI Upskilling & Team Enablement - Stay current on evolving AI tooling (Copilot agents, GenAI models, GCP AI/ML services) and actively share learnings with the broader supply chain team through lunch-and-learns, template sharing, and informal peer coaching.

When applying for this position, please ensure you use your external-facing profile / resume to avoid screening rejection.

Required Qualifications

  • Bachelor's degree in mechanical/Automobile, Supply Chain, Business, Data Analytics, Industrial Engineering, or a related field
  • 8-12 years of hands-on experience in supply chain operations, supplier management, or procurement delivery
  • Proven ability to make risk-based expediting decisions (air freight, rerouting, safety stock) with a clear cost-risk rationale
  • Practical proficiency with Microsoft Copilot and Office 365 suite (Power Automate, Power BI, Excel, Teams, SharePoint) for creating automations and AI agents
  • Strong analytical and communication skills with the ability to bridge the gap between business needs and technical solutions

Preferred Qualifications (Plus)

  • Exposure to Google Cloud Platform (BigQuery, Looker Studio, Dataflow) for data wrangling and dashboard creation
  • Familiarity with AI/ML concepts (predictive scoring, GenAI prompting, workflow agents)
  • Experience with ERP systems (SAP, Oracle) and supplier scorecard frameworks
  • Prior experience contributing to process automation or digital transformation initiatives
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