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JOB DETAILS

Credit Risk Modeler

CompanyFord Motor Company
LocationChennai
Work ModeOn Site
PostedNovember 9, 2026
About The Company
We don't just make history -- we make the future. Ford put the world on wheels over a century ago, and our teams are re-inventing icons and creating groundbreaking connected and electric vehicles for the next century. We believe in serving our customers, our communities, and the world. If you do, too, come move the world and make the future with us. Ford is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation, we have sought to make the world a better place – one that benefits lives, communities and the planet. We are here to provide the means for every person to move and pursue their dreams, serving as a bridge between personal freedom and the future of mobility. In that pursuit, our 186,000 employees around the world help to set the pace of innovation every day. Privacy Policy: https://www.ford.com/help/privacy/
About the Role

Potential candidates should have knowledge in general math modeling, Machine Learning (ML) and related Operations Research (OR) and simulation techniques. Candidates should have hands-on experience in developing quantitative models. They should possess the ability to translate a business problem into an analytical problem, recommend, implement and validate quantitative models, and generate/deliver insights to stakeholders.  Preference would be given to candidates that are intellectually curious, innovative thinkers, and have demonstrated ability to solve problems independently.  
 

Responsibilities

Roles & Responsibilities

  • Support credit risk analytics activities across model development, independent validation, monitoring, and business reporting.

  • Conduct data extraction, reconciliation, quality checks, and analytical review using tools such as SQL, SAS, Python, Excel, and PowerPoint.

  • Translate analytical findings into clear insights and communicate results to model development, validation, business, and risk stakeholders.

  • Maintain clear documentation of analysis, validation observations, reporting logic, assumptions, and key findings.

  • Assist in the development and enhancement of IFRS 9 models, including PD, LGD, EAD, expected credit loss, and related risk estimation frameworks.

  • Perform independent validation activities by reviewing model methodology, assumptions, input data, outputs, performance, and documentation.

  • Analyze portfolio trends, credit risk drivers, delinquency patterns, default behavior, and model performance indicators to support risk decision-making.

  • Execute recurring business reports, dashboards, and management information packs accurately and within agreed timelines.

Qualifications

Qualifications

  • Masters in Mathematics/Statistics/Economics/Engineering or any other related discipline or a track record of performance that demonstrate this ability
  • Good exposure to ML techniques such as Clustering/classification/decision trees, Random forests and related algorithms
  • Excellent problem solving, communication, and data presentation skills

Skills/Knowledge required

  • Masters in Finance, Financial Engineering, Analytics or Mathematics, Computer Science, Statistics, Industrial Engineering, Operations research, or related field. 

  • Good understanding of Probability of Default (PD), LGD and EAD modeling technique.

  • Very good understanding of Predictive modeling techniques and their application.

  • Statistics and machine learning techniques.

  • Conducted and applied statistical methodologies including linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, cluster analysis

  • Team player and collaboration skills.

  • Programming skills in R, SAS, and PYTHON.

  • Fluency with Excel, PowerPoint and Word 

  • Strong written and oral presentation / communication skills – must have the ability to convey complex information simply and clearly

  • Experience with developing and implementing cloud based analytical solutions in GCP or similar set up.

Experience (Good to have):

  • 3 - 5 Years exposure in Banking & Financial Services industry

  • Candidate should have worked in Credit Analytics (Mandatory) and preferably in Financial Analytics, Retail bank, Mortgage, Lending / liability product

  • Risk Analytics, Credit Risk Scorecard Development, Model Validation, IFRS 9 Validations, Credit Loss Forecasting

 

Key Skills
Credit Risk ModelingMachine LearningSQLSASPythonIFRS 9Predictive ModelingStatistical AnalysisData ExtractionModel ValidationProbability Of DefaultLGDEADOperations ResearchCloud ComputingGCP
Categories
Data & AnalyticsFinance & AccountingTechnologySoftwareConsulting
Job Information
📋Core Responsibilities
The role involves developing, validating, and monitoring credit risk models including IFRS 9 frameworks to support risk decision-making. You will also be responsible for conducting data analysis, generating business reports, and communicating analytical insights to various stakeholders.
📋Job Type
full time
📊Experience Level
2-5
💼Company Size
186127
📊Visa Sponsorship
No
💼Language
English
🏢Working Hours
40 hours
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