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Tier-1 bank and metro location increase competition, but niche credit-risk modeling focus moderates applicant pool.
Role requires credit risk frameworks (CECL/IFRS9) and banking domain expertise, limiting cross-industry transferability.
Explicit 5+ years, mandatory credit-risk modeling experience and Python create strict filtering.
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Lead the maintenance, optimization, and planning of complex quantitative credit risk models including ACL, CECL, IFRS9, Basel, and CCAR for commercial portfolios.
Drive development and execution of model monitoring, production analytics, and strategic infrastructure projects to improve model performance and reporting.
Collaborate cross-functionally to align model schedules and processes with SDLC, compliance, and risk management standards.
5+ years of quantitative modeling experience including credit risk analytics and model operations.
Bachelor’s degree or higher in quantitative field such as applied mathematics, statistics, engineering, finance, economics, econometrics, or computer science.
Advanced programming skills in Python, Tableau, and Power BI.
Work Experience Required: Minimum 5+ years in credit risk modeling or quantitative model operations.
Experienced in leading large-scale credit risk modeling projects and model lifecycle management in complex financial environments.
Demonstrates strong technical expertise and project management abilities to prioritize and deliver under pressure.
Skilled in developing data-driven insights and process improvements with a focus on standardization, automation, and regulatory compliance.