Credit Risk Model Validator — Wholesale & SMB

U.S. Bank; Minneapolis (MN); In loco; USD 105.000 - 124.000; Tempo pieno

Vantaggi offerti da questo lavoro

Healthcare (medical, dental, vision)

Life insurance

Disability insurance

401(k) retirement plan

Paid vacation

Descrizione del lavoro

U.S. Bank is seeking a Quantitative Model Validation Analyst to support independent validation of credit loss forecasting models and risk scorecards across commercial portfolios.

The role emphasizes rigorous analysis, clear documentation, and engagement with stakeholders and regulators. The ideal candidate has advanced quantitative training and experience with Python or SAS, strong data skills, and a track record in model validation, reporting, and continuous improvement within a risk management

Competenze

• Bachelor’s degree in a quantitative field with 5+ years of relevant experience OR
• MA/MS in a quantitative field with 3+ years of related experience OR
• PhD in a quantitative field with <2 years of related experience

Mansioni

• Conduct independent validation of CCAR and CECL credit loss forecasting models for wholesale and small business portfolios.
• Evaluate model conceptual soundness, assumptions, data reliability, performance metrics, monitoring, and testing.
• Design and execute validation testing including benchmarking, sensitivity analysis, and outcome analysis.
• Document validation outcomes and communicate findings to stakeholders and regulators.

Conoscenze

Python

SAS

Data analysis

Model validation

Regression analysis

Documentation

Stakeholder communication

AI tools

Formazione

MA/MS in quantitative field

PhD in quantitative field

Strumenti

SQL

Excel

Jupyter

Git

Descrizione del lavoro

U.S. Bank is seeking a Quantitative Model Validation Analyst to support independent validation of credit loss forecasting models and risk scorecards across commercial portfolios.

The role emphasizes rigorous analysis, clear documentation, and engagement with stakeholders and regulators. The ideal candidate has advanced quantitative training and experience with Python or SAS, strong data skills, and a track record in model validation, reporting, and continuous improvement within a risk management