Quantitative Model Validation Analyst – Credit Risk

U.S. Bank National Association • Minneapolis, MN

1d • Onsite

About The Position

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.
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 (NetCo), 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:

Requirements

• 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.
• 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

Nice To Haves

• 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 financial knowledge such as Mathematical plus finance degrees, Statistic plus Economics, Scientific Computation, Operational research engineering plus business administration.
• Strong statistical programming skills in Python, SAS, R, SQL. A programming certification is a plus.
• Strong oral and written communication skills, capable of addressing both technical and non-technical audience.
• Experience interpreting and applying complex financial regulations or accounting standards.

Responsibilities

• 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.
• develop, validate risk forecasting models, probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), Net Charge-off (NetCo), and Economic Factor Models.
• complete development/validation data compilation and implementation verification
• manage and track recommendations
• delivering and reviewing comprehensive written model technical documents to present outcomes to senior management of related department across the bank and regulatory agencies.

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees