Senior Manager-Credit Risk

Evalueserve, Inc.; Gurugram District; On-site; INR 4,000,000 - 7,500,000; Full time

Job summary

Evalueserve, Inc. is seeking an experienced credit risk professional to lead model development, validation, and regulatory advisory engagements for banks and financial institutions.

The role focuses on PD, LGD, IFRS 9, and Credit Risk RWA with strong leadership and client management. You will guide end-to-end modelling, validation, and reporting, drive automation in Python, supervise a team of analysts, and contribute to business development through proposals and thought leadership, including

Qualifications

• Master’s degree in Statistics, Mathematics, Economics, Financial Engineering, Quantitative Finance, or Data Science or B.Tech./MBA (Finance).
• 7–11 years of experience in credit risk model development and/or validation in banking, consulting, or risk analytics.
• Proven hands-on PD/LGD/EAD modelling and validation experience for Basel IRB and IFRS 9.
• Strong knowledge of IFRS 9 ECL, Credit Risk RWA, Basel III/IV requirements.
• Excellent communication, stakeholder management, and documentation skills.

Responsibilities

• Lead end-to-end development, redevelopment, calibration, and enhancement of PD, LGD, and EAD models for Basel IRB and IFRS 9.
• Oversee independent validation of credit risk models, including data quality, methodology, and back-testing.
• Design IFRS 9 ECL frameworks, lifetime PD, SICR, staging, and macroeconomic scenarios.
• Estimate and monitor Credit Risk RWA under SA and IRB approaches, advice on mitigations.
• Advise on Basel III/IV requirements and impact assessments for standardised and IRB approaches.
• Drive automation of modelling workflows in Python; establish coding standards and reusable libraries.
• Lead model monitoring and annual reviews with KPI thresholds and remediation tracking.
• Review documentation and ensure governance/regulatory compliance.
• Engage with clients as primary contact, manage expectations, and coordinate audits/regulators.
• Mentor analysts and lead teams; manage project planning and delivery.
• Contribute to business development with proposals, POCs, and AI/ML insights in credit risk.

Skills

PD modelling

LGD modelling

EAD modelling

Model validation

IFRS 9 ECL

Python

SAS

SQL

Team leadership

Client management

Communication

Documentation

Education

Master’s in Statistics / Quantitative Finance

B.Tech./MBA (Finance)

Tools

Python

SAS

SQL

Job description

We are looking for an experienced credit risk professional to lead model development, validation, and regulatory advisory engagements for global banks and financial institutions. The role combines deep technical ownership of PD and LGD models, IFRS 9 and Credit Risk RWA frameworks with team leadership, client management, and business development responsibilities.

Key Responsibilities

• Lead end-to-end development, redevelopment, calibration, and enhancement of PD, LGD, and EAD models across retail, SME, and wholesale portfolios for both regulatory (Basel IRB) and accounting (IFRS 9) purposes.
• Lead independent validation of credit risk models, covering conceptual soundness, data quality, methodology, assumptions, performance testing, benchmarking, and outcome analysis, in line with SR 11-7, PRA SS1/23, and client model risk policies.
• Design, review, and challenge IFRS 9 Expected Credit Loss (ECL) frameworks, including lifetime PD term structures, SICR and staging criteria, forward-looking macroeconomic scenarios, scenario weighting, and post-model adjustments.
• Oversee Credit Risk RWA computation and analysis under the Standardised and IRB (F-IRB / A-IRB) approaches, including exposure classification, credit risk mitigation, CCF/EAD treatment, RWA reconciliation, and variance analysis.
• Advise clients on Basel III and Basel IV (Basel III final reforms / CRR3 / Basel 3.1) requirements, and lead impact assessments for the revised Standardised Approach, IRB input floors, IRB scope restrictions, and the output floor.
• Drive automation of model development, validation, and monitoring workflows in Python; define coding standards, perform code reviews, and build reusable analytical libraries.
• Design and lead model monitoring frameworks and annual model reviews, including KPI definition, threshold setting, and remediation tracking.
• Review and sign off model development and validation documentation, ensuring compliance with internal governance and regulatory expectations.
• Act as the primary point of contact for client stakeholders, including model owners, model validation teams, internal audit, and regulators.
• Manage, coach, and mentor a team of analysts and lead analysts; own project planning, quality assurance, and timely delivery.
• Contribute to business development through proposals, solution design, proofs of concept, and thought leadership, including AI/ML applications in credit risk.

Core Technical Focus Areas

• PD and LGD Modelling & Validation: Logistic regression and scorecards, rating master scales, long-run average default rate calibration, margin of conservatism, workout and downturn LGD, cure rates; validation testing such as Gini/AUROC, KS, binomial and Jeffreys tests, Hosmer-Lemeshow, PSI/CSI, and back-testing.
• IFRS 9: ECL methodology, PIT vs. TTC PD conversion, lifetime PD (e.g., Markov chain, survival, vintage approaches), SICR and staging, macroeconomic satellite models, and management overlays.
• Credit Risk RWA: SA and IRB risk-weight functions, asset correlation and maturity adjustment, credit risk mitigation, CCF/EAD, RWA drivers and movement analysis, and capital adequacy reporting.
• Basel III and Basel IV Regulatory Areas: Basel IRB framework, CRR/CRR3, PRA Basel 3.1, EBA guidelines on PD/LGD estimation and definition of default, output floor, input floors, ICAAP, and regulatory stress testing.
• Python: Advanced use of pandas, NumPy, SciPy, statsmodels, and scikit-learn; building reproducible modelling and validation pipelines; ML challenger models (e.g., gradient boosting); version control with Git.

Required Qualifications

• Master’s in Statistics, Mathematics, Economics, Financial Engineering, Quantitative Finance, or Data Science, or B.Tech./MBA (Finance) from a reputed institution.
• 7–11 years of experience in credit risk model development and/or validation in a bank, consulting firm, or risk analytics organisation.
• Proven hands‑on track record in PD and LGD (and EAD) model development and validation for Basel IRB and IFRS 9.
• In-depth knowledge of IFRS 9 ECL, Credit Risk RWA computation, and Basel III / Basel IV requirements.
• Strong understanding of model risk management guidelines such as SR 11-7, PRA SS1/23, and EBA/ECB internal model guidance.
• Advanced, hands‑on proficiency in Python; SAS and SQL experience is good to have.
• Experience leading teams and managing client deliverables end to end.
• Excellent communication, stakeholder management, and documentation skills.

Good to Have

• Professional certification such as FRM, PRM, or CFA.
• Exposure to CECL, CCAR/DFAST, or ICAAP stress testing.
• Experience applying machine learning or GenAI in credit risk modelling and validation.
• Experience working directly with onshore / international client stakeholders.

Disclaimer:

The above job description serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances.

Please Note

We appreciate the accuracy and authenticity of the information you provide, as it plays a key role in your candidacy. As part of the Background Verification Process, we may verify your employment, education, and other details. Please ensure all information is factual and submitted on time. For any assistance, your recruiter is available to support you.