Supply Chain Analyst - Multi-Tier Risk & Data Specialist

Job Description As an Analyst in the N-Tier Risk Sensing CoE at Ford, your primary responsibility is to ensure the continuity of Ford's production by maintaining visibility across the multi-tier supply chain. Your role involves providing real-time insights to mitigate risks before they impact production, thereby supporting executive decision-making. Working collaboratively within a high-performance team, you are expected to be agile and a valuable team player who can translate complex datasets into actionable intelligence. **Key Responsibilities:** - **Technical Execution - Network Mapping & Data Analysis** - Execute deep-dive mapping of supply chains, specifically for complex electronic 'Black Boxes' and critical commodities, identifying suppliers at Tier 2, 3, and beyond. - Validate supplier-provided data by cross-referencing industry intelligence, logistics feeds, and historical performance to establish a 'single source of truth' for the supply chain. - Identify 'Single Point of Failure' nodes within the sub-tier network, focusing on regional concentrations and capacity constraints. - Utilize data science methodologies to identify regional concentrations, geopolitical vulnerabilities, and supply chain constraints. - **Operational Management** - Maintain high standards for 'Time-to-Recover' on risk assessments and ensure the 'Risk Prediction Accuracy' of your assigned commodity portfolios. - Manage end-to-end data workstreams with technical precision in an agile, high-pressure environment. - Assist in developing proactive mitigation playbooks by providing data-backed foundations for derisking and regionalization strategies. - **Digital Integration & Collaboration** - Collaborate with IT partners to integrate cleaned, validated N-Tier data into Fords AI-driven resilience dashboards. - Provide technical data support to Global Purchasing, Engineering, and Material Planning and Logistics teams during supply crises or strategic sourcing reviews. - Create high-impact data visualizations to simplify complex supply chain dependencies for senior management briefings. **Qualifications Required:** - **Education:** B.E./B.Tech in a Technical/Engineering field is required. Specialization in Supply Chain Operations Research is an additional advantage. Data Science knowledge is preferable. - **Experience:** 36 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. In addition to the above, the role requires working in shifts from 2:00 PM 11:30 PM (IST) to ensure daily synchronization with North American and European stakeholders. The environment is described as a high-paced, data-centric Global Capability Center (GCC), where you must be adaptable to pivot quickly in response to global geopolitical or environmental risks. This position is at a Senior Level, reflecting the need for a seasoned professional with extensive experience in supply chain analytics and risk management. As an Analyst in the N-Tier Risk Sensing CoE at Ford, your primary responsibility is to ensure the continuity of Ford's production by maintaining visibility across the multi-tier supply chain. Your role involves providing real-time insights to mitigate risks before they impact production, thereby supporting executive decision-making. Working collaboratively within a high-performance team, you are expected to be agile and a valuable team player who can translate complex datasets into actionable intelligence. **Key Responsibilities:** - **Technical Execution - Network Mapping & Data Analysis** - Execute deep-dive mapping of supply chains, specifically for complex electronic 'Black Boxes' and critical commodities, identifying suppliers at Tier 2, 3, and beyond. - Validate supplier-provided data by cross-referencing industry intelligence, logistics feeds, and historical performance to establish a 'single source of truth' for the supply chain. - Identify 'Single Point of Failure' nodes within the sub-tier network, focusing on regional concentrations and capacity constraints. - Utilize data science methodologies to identify regional concentrations, geopolitical vulnerabilities, and supply chain constraints. - **Operational Management** - Maintain high standards for 'Time-to-Recover' on risk assessments and ensure the 'Risk Prediction Accuracy' of your assigned commodity portfolios. - Manage end-to-end data workstreams with technical precision in an agile, high-pressure environment. - Assist in developing proactive mitigation playbooks by providing data-backed foundations for derisking and regio