{"description": " Job Description
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.

6. 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 Strong 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!", "salary_raw": "Row(double=None, string=None)"}