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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 bank, metro location, mid-level experience, but niche regulatory quant skills limit candidate pool.
Requires banking regulatory modeling (CCAR/CECL) and credit risk expertise, limiting cross-industry transferability.
Explicit 4+ years, regulatory model requirements, and mandatory Python/SQL enforce strict shortlisting.
Job Description
Structured overview of role & requirementsAbout This Role
Lead development, implementation, and documentation of complex regulatory credit risk models (CCAR, CECL, IFRS) for commercial portfolios.
Analyze and forecast losses, compute capital requirements, and contribute to model validation and regulatory compliance efforts.
Collaborate with auditors, regulators, and cross-functional teams to improve data, modeling processes, and strategy discussions on risk analytics.
Minimum Requirements
Bachelor's degree or higher in a quantitative discipline (mathematics, statistics, engineering, physics, economics, computer science, or related).
4+ years of quantitative analytics experience involving predictive modeling and statistical analysis.
Required programming skills include at least 2+ years hands-on experience with Python and SQL.
Experience or knowledge in credit risk modeling, regulatory model development, and banking domain strongly preferred.
Ideal Candidate Profile
Experienced quantitative analyst with exposure to credit risk modeling within banking/commercial portfolios.
Strong operational focus on regulatory compliance, model validation, and audit governance in a complex, dynamic environment.
Capable of deep technical collaboration with regulators, auditors, and business teams, emphasizing data-driven model development and enhancement.