Join our Regulatory & Financial Risk team in Kolkata as a Deputy Manager, Credit Risk Quant. You will play a crucial role in validating advanced Internal Ratings-Based (IRB) models, ensuring their accuracy and compliance with regulatory standards. This position offers a unique opportunity to influence risk management strategies within a leading financial institution.

This role focuses on the independent validation of complex credit risk models, including those for Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and Credit Conversion Factors (CCF). You will assess the soundness of rating system designs, RWA attribution, and capital impact, contributing to robust financial risk assessment.

Perform independent validation of Advanced IRB/Foundation IRB models, focusing on PD, LGD, EAD, and CCF methodologies. Assess rating system design, performance, RWA attribution, and capital impact. Evaluate model assumptions for diverse wholesale product exposures, including corporate, SME lending, project finance, and financial institutions.

Review and challenge model segmentation, downturn calibration, and the treatment of collateral and guarantees. Ensure compliance with Basel III/IV IRB requirements and regional supervisory rules. Conduct model performance testing and prepare high-quality validation documentation with clear findings and remediation actions. Support regulatory engagements and collaborate with internal teams to ensure model fitness-for-purpose.

Candidates should possess experience with corporate lending, project finance, commercial real estate, and private equity exposures. Familiarity with stress testing frameworks (CCAR/ICAAP) and IRB-to-IFRS 9 model linkages is beneficial. The ability to articulate quantitative findings to non-technical senior stakeholders is essential.

Strong analytical judgment, high attention to detail, and excellent written communication skills are paramount. A Master’s degree or higher in a quantitative field such as Finance, Statistics, Mathematics, or Engineering is desired, along with 4-6 years of experience in modelling or validation of Wholesale IRB capital models. Proficiency in Python, R, SAS, SQL, and credit modelling statistics is required.