Credit Risk Modeling Specialist

• Develop, review, and validate credit risk measurement models under the Internal Ratings-Based (IRB) approach, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD); implement credit risk-weighted asset (RWA) calculations under both the IRB and Standardized Approach (SA).
• Develop, review, and validate credit risk models in accordance with IFRS 9, including PD, LGD, and EAD models, and implement Expected Credit Loss (ECL) estimation.
• Develop, review, and validate credit risk models applied throughout the credit lifecycle, from customer targeting, credit assessment and approval to credit monitoring, debt collection, and recovery.
• Implement credit risk models in business operations and risk management activities, with a particular focus on digital transformation initiatives.
• Operate and maintain internal credit rating systems and credit risk modeling platforms; conduct use testing to ensure the effective application of credit risk models.

Job Requirements

Education

• Bachelor's degree or higher, with a minimum Good academic classification (or equivalent), from a reputable domestic or international university.
• Major in Financial Mathematics, Mathematical Economics, Finance and Banking, Risk Management, or related disciplines.

Experience

• Preference will be given to candidates with experience in commercial banks, financial institutions, or auditing firms, particularly in:

• Development and operation of internal credit rating systems.

• Development and implementation of credit risk measurement tools.

• Credit risk management and analytics.

Skills and Competencies

Core Competencies:

• Strong mathematical and statistical analysis skills, including statistical model development.
• Proficiency in data processing, data management, and data structures.
• Ability to present and visualize data analysis results effectively.

Additional Competencies:

• Sound understanding of credit risks throughout the credit lifecycle and credit risk analysis methodologies.
• Proficiency in database query languages and statistical analysis software.
• Strong communication and collaboration skills, with the ability to work effectively with credit risk management, credit risk monitoring, and business units