Quantitative Model Validation Analyst – Credit Risk

Quantitative Model Validation Analyst – Credit Risk page is loaded## Quantitative Model Validation Analyst – Credit Risk locations:
Minneapolis, MN:
Charlotte, NCtime type:
Full time posted on:
Posted Todaytime left to apply:
End Date:
February 10, 2026 (11 days left to apply) job requisition :
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.

Try new things, learn new skills and discover what you excel at—all from Day One.##
** Job Description
** This role will be part of a highly visible and dynamic quantitative risk function within U.S. Bank that leads Stress Testing (CCAR) and Current Expected Credit Losses (CECL) estimations. The primary duty of the job is to create, validate, test, document, implement and/or oversee usage of complex statistical models that are used as part of financial decision-making process. Deliverable to regulatory and senior management includes the creation of comprehensive written reports, modeling code, business requirements, monitoring reports and related code, and procedures.
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* Job Description:

** This position will work on a combination of Stress Testing (CCAR) and Credit Expected Credit Losses (CECL) estimations statistical models. The role requires to develop, validate risk forecasting models, probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), Net Charge-off (Net Co), and Economic Factor Models.

This role emphasizes complex statistical models under CCAR stress testing guidance and CECL ASU rule. This role requires experience with development process, quarterly continuous monitoring process, inaugural validation process, and capital reconciliation process. Also, the role requires knowledge of the bank’s reporting data system to complete development/validation data compilation and implementation verification, and experience to manage and track recommendations.

Specifically:

Three plus years of large size commercial bank working experience in risk model validation. Advanced experience of financial statistical modeling methods (Hazard models, Regression models, Decision Tree models, Time Series, Machine Learning, etc.) Related experience with Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models for CCAR and CECL.

Working experience in CCAR and CECL estimation for both retail and wholesale portfolios, including portfolio such as Residential Mortgage, Consumer Credit Cards/Lines, Wholesale C&I, Wholesale CRE, and Small Business. Familiar with the bank reporting and data system. Have advanced ability to deal with large data and complete model validation and implementation verification process. Ability to write and enhance automated testing programs for model performance assessment.
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* 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
** An advanced quantitative field degree (MA/MS or PHD) is required. The role should have financial industry experience in statistical programming including Python, SAS, R, and SQL. The analyst is also responsible for ensuring models are consistent with the bank’s risk management policies, procedures, and practices by directly interacting with model owners, senior managers such as portfolio risk management, corporate finance, external reporting, audit services, and industry experts, which requires advanced level of presentation, relationship building, and negotiation skills.
* Advanced degree in quantitative discipline (MS/MA/PHD).
* This role prefers education background to cover both quantitative skills and business or…