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Tier-1 bank and metro location but niche credit-risk specialization reduces applicant pool.
Requires specialized credit risk and regulatory validation experience, limiting cross-industry transferability.
Mandates 7–10 years, regulatory IRB/IFRS9 expertise and specific SAS/R/Python/SQL skills.
Lead validation of credit risk models including IRB, IFRS9, and stress testing, ensuring adherence to internal and regulatory standards.
Design and execute validation plans covering data quality, model methodologies, performance, and compliance across the model lifecycle.
Provide mentorship and technical leadership within the Model Risk & Validation team and contribute to strategic transformation and continuous improvement initiatives.
7-10 years of experience in credit risk model validation or development involving IRB, IFRS9, and stress testing models.
Bachelor's or Master's degree in quantitative disciplines such as mathematics, statistics, econometrics, or engineering in Computer Science/Information Technology.
Proficiency in SAS, R, Python, and SQL programming languages.
Essential knowledge of Basel regulatory standards on credit risk; experience with APRA regulations on IRB, IFRS9, and stress testing is advantageous.
Experienced in end-to-end delivery of quantitative projects within credit risk model validation.
Ability to effectively communicate complex validation findings and recommendations to diverse stakeholders.
Familiarity with modern analytics tools such as Jupyter notebooks, R-markdown, GitHub, and usage of AI-assisted coding tools like copilot, GPT, Claude.