Purchase Analyst

Job Description

As an Analyst in the N-Tier Risk Sensing CoE, you are a strategic specialist responsible for securing Ford’s production continuity through multi-tier supply chain visibility. In the current dynamic automotive landscape, your role is to provide real-time, proactive insights that eliminate risk before it impacts production. Working within a high-performance team, you are required to be agile and amicable team player. You will transform complex datasets into actionable intelligence, enabling executive leadership to make informed, strategic decisions.

Responsibilities

Technical Execution - Network Mapping & Data Analysis

• Multi-Tier Illumination: Execute deep-dive mapping of supply chains for complex electronic "Black Boxes" and critical commodities, identifying suppliers at Tier 2, 3, and beyond.
• Supplier Intelligence: Validate supplier-provided data by cross-referencing industry intelligence, logistics feeds, and historical performance to ensure a "single source of truth" for the supply chain.
• Vulnerability Assessment: Identify "Single Point of Failure" nodes within the sub-tier network, focusing on regional concentrations and capacity constraints
• Risk Modeling: Utilize data science methodologies to identify regional concentrations, geopolitical vulnerabilities, and supply chain constraints.
  
  
  

• KPI Delivery: Maintain high standards for "Time-to-Recover" on risk assessments and ensure the "Risk Prediction Accuracy" of your assigned commodity portfolios.
• Extreme Ownership: Manage end-to-end data workstreams with technical precision in an agile, high-pressure environment.
• Playbook Support: Assist in the development of proactive mitigation playbooks by providing the data-backed foundation for derisking and regionalization strategies.
  
  
  

• AI Integration: Collaborate with IT partners to feed cleaned, validated N-Tier data into Ford’s AI-driven resilience dashboards.
• Cross-Functional Support: Provide technical data support to Global Purchasing, Engineering, and Material Planning and Logistics teams during supply crises or strategic sourcing reviews.
• Visualization: Create high-impact data visualizations that simplify complex supply chain dependencies for senior management briefings.
  
  
  

• Education: B.E./B.Tech in a Technical/Engineering field (Required); Specialization in Supply Chain Operations Research is an additional advantage. Data Science knowledge is preferable.
• Experience: 3–6 years of experience in Supply Chain analytics, Commodity Management, or Risk Management—ideally within the Automotive, Electronics, or Aerospace sectors.
• Technical Skills: Proficiency in data visualization tools (e.g., Power BI, Tableau), SQL, and advanced Excel. Familiarity with AI/Machine Learning applications in SCM is highly preferred.
• Domain Knowledge: Understanding of global supplier ecosystems, electronic component manufacturing, or raw material markets.
• Shift: 2:00 PM – 11:30 PM (IST). This is critical for daily synchronization with North American and European stakeholders to ensure a "follow-the-sun" risk monitoring model.
• Environment: A high-paced, data-centric Global Capability Center (GCC). You must be comfortable pivoting quickly as global geopolitical or environmental risks emerge.