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Tier-1 bank, Bangalore, mid-level data role with common title increases applicant density.
Role requires credit risk and regulatory domain expertise, limiting cross-industry transferability.
Explicit 2–4 years, mandatory credit-risk validation, regulatory standards and specific tools enforce high shortlisting strictness.
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Lead validation activities for credit risk models including IRB, IFRS9, and Stress Testing to ensure data quality, methodology soundness, model performance, and regulatory compliance throughout the model lifecycle.
Engage with internal stakeholders such as model developers and owners to communicate validation findings, risks, and recommendations effectively.
Drive strategic transformation and continuous improvement initiatives in the validation function to enhance workflow efficiency, methodology robustness, and the quality and consistency of validation outcomes.
2-4 years of credit risk model validation or development experience specifically with IRB, IFRS9, and stress testing models.
Bachelor's or Master's degree in Computer Science, Information Technology, mathematics, statistics, econometrics, or a related quantitative discipline.
Proficiency in programming languages/tools including SAS, R, Python, SQL, and familiarity with Jupyter notebooks or R-markdown; experience with GitHub is advantageous.
Essential knowledge of Basel regulatory standards on credit risk; experience with APRA regulations on IRB, IFRS9, and stress testing preferred.
Experience working within a model risk and validation framework focusing on credit risk models, demonstrating end-to-end project delivery.
Strong quantitative and programming skills applied to complex financial risk model validation in a regulated environment.
Ability to communicate complex model validation findings clearly to diverse stakeholders and contribute to improving validation processes and methodologies.