Website Ford
Analytics Integration Analyst — Ford Motor Company
Company: Ford Motor Company
Division: Global Data Insight & Analytics (GDIA) / Credit Risk Analytics
Role Title: Analytics Integration Analyst (Job ID: 73738)
Location: Chennai, Tamil Nadu, India
Work Mode: On-Site / Full-Time
Experience Level: 3+ Years of experience in credit risk analytics, model implementation, or analytics solutions integration
Educational Requirement: Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or related field (Master’s degree preferred)
Core Tool Stack: SAS (SAS Real-Time Decision Manager), SQL, Python, Relational Databases (RDBMS), Mainframe Systems (JCL, VSAM, Flat Files)
Cloud & Automation Stack: Google Cloud Platform (GCP: BigQuery, Cloud Storage, Cloud Functions, Cloud Composer, Cloud Run), GenAI Tooling / LLM Workflows, Linux, CI/CD Automated Validation
About Ford Motor Company & GDIA
Ford Motor Company is a global automotive enterprise driving mobility innovation, digital vehicle services,and enterprise analytics worldwide. Ford’s Global Data Insight & Analytics (GDIA) organization in Chennaiserves as the technology engine for data science, model deployment, financial credit risk analytics, and global operational decisioning.
Role Overview
Ford Motor Company is recruiting a detail-oriented Analytics Integration Analyst to join its GDIA organization in Chennai.
This role bridges model development, IT infrastructure, and business execution. You will implement, validate, test, and productionize predictive credit risk models and risk strategies (e.g., scorecards, PD, LGD, EAD, ECL under CECL/IFRS 9) across global enterprise platforms. You will build automated data pipelines connecting mainframe legacy datasets with Google Cloud Platform (GCP), leverage Python and GenAI/LLM tools to simplify testing workflows, and maintain strict model governance standards.
Key Responsibilities
Model Implementation & Productionization
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Model Deployment: Implement, test, validate, and maintain predictive models and risk strategies (Probability of Default, Loss Given Default, Exposure at Default, Expected Credit Loss).
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Cross-Functional Bridge: Collaborate directly with Data Scientists, Business leads, and IT engineering to ensure seamless, accurate transitions from development to production execution.
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Impact Analysis & Reconciliation: Perform data reconciliation, backtesting, regression testing, and impact analysis to resolve implementation edge cases and operational discrepancies.
Pipeline Automation & Legacy-to-Cloud Integration
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Automated Batch Testing: Design and execute automated batch testing workflows linking legacy mainframe environments (JCL, VSAM, flat files) with modern cloud platforms.
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Cloud Architecture (GCP): Leverage GCP services—including BigQuery, PostgreSQL, Cloud Functions, Cloud Storage, Cloud Composer, Cloud Run, and Pub/Sub—to build scalable analytics pipelines.
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GenAI Workflow Enhancements: Develop reusable scripts utilizing SQL, Python, and GenAI/LLM-enhanced logic to compare, summarize, and validate high-volume transaction datasets.
Governance & Continuous Improvement
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Model Risk Management: Maintain detailed technical and process documentation, supporting internal audits, model risk governance, and regulatory compliance.
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Process Optimization: Build proof-of-concepts (PoCs) to streamline delivery workflows, eliminate manual testing toil, and drive process modernization.
Candidate Qualifications & Requirements
Required Qualifications & Experience
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Education: Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field (Master’s degree preferred).
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Experience: 3+ years of hands-on experience in credit risk analytics, model implementation, or analytics integration.
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Programming Skills: Strong programming experience with SAS (preferably SAS Real-Time Decision Manager), SQL, and Python across procedural and object-oriented paradigms.
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Domain & Governance Knowledge: Basic understanding of credit risk concepts (IFRS 9 / CECL, PD, LGD, EAD, ECL), model risk management, and relational database systems.
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Linux & Environment Skills: Working knowledge of Linux systems, IT testing environments, and automated validation.
Preferred Qualifications
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Hands-on experience with Google Cloud Platform (GCP) services (BigQuery, Cloud Storage, Cloud Functions).
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Experience integrating processes involving legacy mainframe systems.
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Exposure to GenAI/LLM tooling and agentic workflow automation.
Role Summary
| Attribute | Details |
| Job Title | Analytics Integration Analyst (Job ID: 73738) |
| Company | Ford Motor Company |
| Division | Global Data Insight & Analytics (GDIA) |
| Location | Chennai, Tamil Nadu, India |
| Experience | 3+ Years |
| Primary Skill Stack | SAS (RTDM), SQL, Python, GCP (BigQuery), Mainframe Systems, Linux |
| Domain Focus | Credit Risk Analytics (IFRS 9 / CECL), Model Implementation, Batch Pipeline Automation, GenAI Workflows |
