Key Responsibilities

1.

Model

Development & Enhancement o Develop and implement advanced quantitative models for assessing credit risk, including models for PD, LGD, and EAD.

o Work with large datasets to develop models that estimate credit risk exposure, focusing on accuracy, robustness, and predictive power.

o Design and refine models to calculate Expected Credit Loss (ECL) under IFRS 9 and CECL frameworks, ensuring compliance with accounting and regulatory standards.

o Continuously monitor and enhance existing models based on new data, market conditions, and regulatory changes.

2.

Model

Validation & Backtesting o Validate and backtest credit risk models, ensuring they meet the required standards for accuracy, consistency, and reliability.

o Develop validation frameworks for assessing model performance and ensuring models accurately reflect credit risk under different economic conditions.

o Provide documentation of model assumptions, methodologies, and limitations, ensuring transparency and compliance with internal governance and regulatory requirements.

o Conduct periodic performance reviews and backtesting of models to ensure they continue to perform well over time and align with actual credit losses.

3.

Expected Credit

Loss (ECL) Modeling o Lead the development of ECL models, calculating the credit loss provisions for financial instruments in line with IFRS 9 or CECL.

o Develop robust methodologies for estimating PD, LGD, and EAD at a granular level (e.g., loan type, sector, region), while incorporating macroeconomic factors.

o Collaborate with accounting, finance, and credit risk teams to integrate ECL models into the firm’s risk management and financial reporting processes.

o Ensure that the ECL models reflect appropriate segmentation of portfolios and the application of relevant adjustments for forward-looking information.

4.





Credit Risk Stress

Testing o Lead the design and execution of credit risk stress testing processes to assess the resilience of credit portfolios under extreme but plausible scenarios.

o Develop and implement stress testing models for key credit risk metrics such as PD, LGD, and

EAD under different macroeconomic and market scenarios.

o Collaborate with other risk teams to define relevant stress test scenarios, including both regulatory scenarios (e.g., CCAR, EBA) and internal stress scenarios.

o Analyze stress test results and present findings to senior management, providing actionable insights on portfolio risk, capital adequacy, and mitigation strategies.

5.

Model

Governance & Regulatory Compliance o Ensure that all credit risk models adhere to regulatory requirements, including Basel III, IFRS 9,

CECL, and other relevant global or local regulations.

o Contribute to internal and external model audits and provide clear documentation on model assumptions, validation processes, and limitations.

o Stay up-to-date with regulatory changes and industry best practices to ensure models remain compliant with evolving standards and regulations.

o Assist in the preparation of regulatory reports and disclosures related to credit risk modeling and stress testing.

- Collaboration & Stakeholder Engagement o Collaborate with other departments (e.g., credit risk, finance, accounting, and IT)



to ensure that models are integrated effectively into day-to-day operations and decision-making.

o Provide support to senior management in understanding model outcomes, advising on risk mitigation strategies, and supporting strategic decision-making.

o Provide expert advice on the application and interpretation of credit risk models, both to technical teams and non-technical stakeholders.

Qualifications

- Education: Master’s or PhD in Quantitative Finance, Financial Engineering, Mathematics, Statistics, or a related field. Professional certifications (e.g., CFA, FRM) are a plus. Candidates with proficiency in VBA,

Python, SAS will be preferred.

- Experience:

o Minimum of 3-5 years of experience in quantitative risk modelling, with a focus on credit risk,

PD, LGD, EAD models, and stress testing.

o Proven experience with the development and validation of ECL models under IFRS 9, CECL, or similar regulatory frameworks.

o Hands-on experience with credit risk stress testing methodologies and model implementation.

o Strong background in working with large financial datasets and using statistical modeling techniques to assess and manage risk.

- Technical Skills:

o Proficiency in programming languages such as Python, R, MATLAB, or SAS for model development and data analysis.

o Solid experience with data analysis tools (e.g., SQL, Excel, Hadoop, Spark) and machine learning libraries (e.g., scikit-learn, TensorFlow).

o Familiarity with credit risk management platforms (e.g., Moody’s, S&P;, Bloomberg) and risk analytics tools.

o Strong understanding of financial statements, credit ratings, and macroeconomic factors influencing credit risk.

Join us in shaping the future of Financial Risks and making a meaningful impact in industry. Apply now to join our collaborative and forward-thinking team!

📌 Manager (Mumbai)
🏢 Uniqus Consultech
📍 Mumbai