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Tier-1 bank in metro with specialized credit-risk modeling reduces broad applicant pool.
Role requires domain-specific regulatory credit risk expertise, limiting cross-industry transferability.
Explicit 5+ years, mandatory regulatory credit-model experience, and specific tech stack make filters strict.
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Lead complex model maintenance, optimization, and planning initiatives for Retail portfolios, ensuring compliance with system development life cycle, security, and regulatory requirements.
Develop and implement strategies for credit risk and predictive models including CECL, IFRS9, Basel, and CCAR stress testing, with responsibility for execution, monitoring, and analytical insights.
Drive process improvements, dashboard development, and collaboration across teams to enhance model performance analysis, reporting, and business loss forecasting.
5+ years of quantitative model solutions or operations experience.
Bachelor's degree from a premier institute or Masters/PhD in applied mathematics, statistics, engineering, finance, economics, econometrics, or computer sciences.
Experience in credit risk analytics or credit risk modeling/monitoring/implementation.
Advanced programming skills in Python, SAS, and SQL.
Strong background in credit risk modeling specifically in retail banking segments like Home Lending, Auto, Cards, and Personal Loans.
Proven ability to lead high performing quantitative analytics teams and manage stakeholder relationships in a dynamic environment.
Demonstrated experience with regulatory model frameworks (CCAR, CECL, IFRS9, Basel) and knowledge of SR 15-18 and SR 11-7 guidelines.