Quantitative Model Validation Analyst - Wholesale & Small Business Credit Loss

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed.  We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career.

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Job Description We are looking for someone who is curious, motivated to learn, and brings a positive, collaborative attitude to our Wholesale and Small Business Model Validation team. The role sits within the Model Risk Management department, part of the Risk Management and Compliance organization at U.S. Bank. As a Quantitative Model Validation Analyst, you will support the independent validation of CCAR and CECL credit loss forecasting models and risk rating scorecard models across commercial portfolios.

These models are foundational to enterprise credit risk assessment, loss forecasting, reserving, and capital planning, offering a unique opportunity to deliver high-impact insights through rigorous analysis, clear documentation, and strong stakeholder engagement.

Key Responsibilities:

Conduct independent validation of the Bank’s wholesale and small business portfolio credit loss forecasting models supporting CCAR stress testing and CECL requirements.

Evaluate model conceptual soundness, the reasonableness of assumptions, the reliability of data, the appropriateness of performance metrics, the effectiveness of model monitoring, and the adequacy of implementation testing.

Design and execute validation testing, including benchmarking, sensitivity analysis, and outcome analysis, to assess model limitations, uncertainty, assumption risk, and forecast reasonableness.

Identify emerging risks and assess the impact of evolving market conditions on model performance, conducting research to evaluate potential model degradation and associated model risk.

Document and communicate validation outcomes and findings, ensuring model risks are accurately identified, timely escalated, and clearly understood by stakeholders and regulators.

Support departmental initiatives to enhance validation practices, streamline validation processes, and leverage advanced tools and technologies to improve efficiency and effectiveness. Basic Qualifications
- Bachelor’s degree in a quantitative field, and five or more years of relevant experience OR - MA/MS in a quantitative field, and three or more years of related experience OR
- PhD in a quantitative field, and less than two years of related experience

Preferred Skills/Experience
- Master’s or Ph.D. degree in a quantitative discipline with a strong academic record.

- Proficiency in Python, SAS, or other analytical programming languages.

- Experience working with complex datasets, regression methodologies, and statistical diagnostic tests.

- Strong technical writing and communication skills, with attention to detail in documentation and reporting.

- Experience leveraging AI tools and agents to support coding, research, and process efficiency.

- Strong problem-solving and research skills, with the ability to investigate complex issues, identify root causes, and develop practical business solutions.

- Ability to work independently and collaboratively in a team environment, manage multiple priorities, and respond effectively to time-sensitive requests.

LOCATION EXPECTATIONS:  This role requires working from a U.S. Bank Location three (3) or more days per week.

If there’s anything we can do to accommodate a disability during any portion of the…