Model Validation Analyst - Credit Loss for Wholesale & SMB

US Bank; Minneapolis (MN); On-site; USD 120,000 - 160,000; Full time

Job summary

U.S. Bank in Minneapolis seeks a Quantitative Model Validation Analyst to support independent validation of CCAR and CECL credit loss forecasting models for wholesale and small business portfolios. The role focuses on rigorous analysis, documentation, and clear communication with stakeholders.

The position requires advanced quantitative education and hands-on experience with validation, data and method evaluation, and collaboration with risk teams and regulators.

Qualifications

• Bachelor's degree in a quantitative field with 5+ years of relevant experience.
• MA/MS in a quantitative field with 3+ years of related experience.
• PhD in a quantitative field with less than 2 years of related experience.
• Experience with CCAR and CECL validation is preferred.

Responsibilities

• Conduct independent validation of wholesale and small business portfolio credit loss forecasting models supporting CCAR stress testing and CECL requirements.
• Evaluate model conceptual soundness, data reliability, performance metrics, monitoring, and implementation testing.
• Design and execute validation testing, including benchmarking, sensitivity analysis, and outcome analysis.
• Identify emerging risks and assess impact of evolving market conditions on model performance.
• Document and communicate validation outcomes and findings to stakeholders and regulators.
• Support initiatives to enhance validation practices and leverage advanced tools and technologies.

Skills

Technical writing

Communication

Independence

Education

Bachelor's degree in a quantitative field

MA/MS in a quantitative field

PhD in a quantitative field

Tools

Python

SAS

AI tools

Job description

U.S. Bank in Minneapolis seeks a Quantitative Model Validation Analyst to support independent validation of CCAR and CECL credit loss forecasting models for wholesale and small business portfolios. The role focuses on rigorous analysis, documentation, and clear communication with stakeholders.

The position requires advanced quantitative education and hands-on experience with validation, data and method evaluation, and collaboration with risk teams and regulators.