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Supply Chain Analyst

Ford

Supply Chain Analyst

Ford

Chennai, Tamil Nadu, India, IN

·

On-site

·

Full-time

·

5d ago

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.

  • 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.

  • 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.

Operational Management

  • 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.

Digital Integration & Collaboration:

  • 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.

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About Ford

Ford

Ford

Public

The Ford Motor Company is an American multinational automobile manufacturer headquartered in Dearborn, Michigan, United States. It was founded by Henry Ford and incorporated on June 16, 1903.

10,001+

Employees

Chennai

Headquarters

$48B

Valuation

Reviews

3.4

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.9

Management

2.3

45%

Recommend to a Friend

Pros

Good pay and benefits

Decent work-life balance options

Learning and advancement opportunities

Cons

Poor management and favoritism

Mandatory overtime and exhausting schedules

Limited growth opportunities

Salary Ranges

36 data points

Mid/L4

Senior/L5

Mid/L4 · ADAS Data Analytics Engineer

1 reports

$132,847

total / year

Base

$102,190

Stock

-

Bonus

-

$132,847

$132,847

Interview Experience

5 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Offer Rate

40%

Experience

Positive 40%

Neutral 40%

Negative 20%

Interview Process

1

Phone Screen

2

Technical Interview

3

Behavioral Interview

4

Final Round Interview

Common Questions

Behavioral

Technical

Assessment