Credit Risk Analyst

Coforge; Gurugram District; On-site; INR 2,000,000 - 3,600,000; Full time

Job summary

Coforge is seeking a candidate to lead end-to-end model development and independent validation across credit, market, operational and fraud risk. You will own MRM engagements, ensure regulatory alignment, and validate internal and vendor models for a US bank, using Python, R, SAS and SQL.

The role emphasizes developing benchmark models with advanced statistics and working closely with clients to present findings and strategic recommendations.

Qualifications

• Master's degree in a quantitative discipline is mandatory.
• 5-7 years hands-on experience in model development, validation and risk management across multiple risk types.
• Proficiency in Python, R, SAS, SQL and ETL tools for data manipulation and modeling.

Responsibilities

• Lead end-to-end model development and independent validation initiatives across credit, market, operational and fraud risk.
• Own delivery of MRM engagements, ensuring timely execution and regulatory alignment (SR 11-7, Basel IRB, CCAR, IFRS9).
• Independently validate internal and vendor models for a US bank for robustness and suitability.
• Develop benchmark models using advanced statistics and ML techniques to challenge primary models.
• Manage client communications, gathering requirements and presenting validation findings with recommendations.

Skills

Model development

Model validation

Risk management

Education

Master's degree in quantitative discipline

Tools

Python

R

SAS

SQL

ETL tools

Job description

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Responsibilities

• Lead end-to-end model development and independent validation initiatives across credit risk, market risk, operational risk and Fraud risk (PD, LGD, EAD, CECL, Stress Testing, AML, Fraud, Scorecards, ECAP, CCAR etc.).
• Own the delivery of MRM engagements, ensuring timely execution, quality assurance, and alignment with regulatory standards (SR 11-7, Basel IRB, CCAR, IFRS9).
• Independently validate internal and vendor models for a US bank, applying rigorous conceptual and quantitative assessments to ensure robustness, reliability, and suitability for intended use.
• Develop benchmark models using advanced statistical and machine learning techniques to challenge and validate primary models.
• Manage client communications, including requirement gathering, progress updates, presentation of validation findings, and strategic recommendations.

Qualifications

• 5-7 years of hands‑on experience in model development, validation, and risk management across different types of risks (credit, market, operational and fraud).
• Strong understanding of regulatory guidelines and compliance frameworks (SR 11-7, OCC, CECL, Basel, IFRS9).
• Proficiency in Python, R, SAS, SQL, and ETL tools for data manipulation and model development.
• Master?s degree in a quantitative discipline (Statistics, Economics, Finance, Data Science, etc.) (MUST HAVE).