US Bank Looking for Sr. Quantitative Model Validation Analyst – Financial Crimes/Compliance at Minneapolis, MN Full Time

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 position is an individual contributor role residing within the Bank’s Second Line of Defense Risk Management and Compliance organization. Specifically, this position supports the Model Risk Management (“MRM”) program at the Bank. The overall MRM program is designed to provide governance and control to manage financial models and associated risks that may impact the company, including financial, liquidity, market, operational, reputational, strategic, and other risks as appropriate. Validation Analysts within MRM provide independent validation of models that the Bank relies on for making financial decisions. A robust and comprehensive model validation comprises steps that independently challenge a model’s conceptual framework and methodology, data used in the model, implementation process, as well as model usage and performance. The validation process also identifies corrective actions to ensure timely remediation of model risk.

The individual in this position works with Model Owners and Developers to validate models related to the Bank’s Financial Crimes (Anti-Money Laundering, Economic Sanctions/OFAC) and Compliance (Fair Lending) programs, adhering to OCC 2011-12 Regulatory Guidance and USB’s Model Risk Management Policy and Standards. The Analyst will document and present the model validation observations and outcomes to Model Owners/Developers, as well as interface with key stakeholders, regulators (OCC/FRB), and internal auditors to discuss these reported observation and published outcomes.

Essential Functions

• Demonstrated ability to work independently as well as within collaborative groups.
• Strong project management skills.
• Has advanced understanding, and can apply knowledge of, complex mathematical techniques (but not limited to): statistical outlier methods, logistic regression, natural language processing (NLP), and various machine learning methods (e.g., random forest, XGBoost, etc.) and other ensemble techniques.
• Experience operating and validating both internally built models customized for the application and off-the-shelf third-party proprietary vendor methods.
• Can work Independently to validate, test, document, and/or oversee usage of advanced quantitative models. Deliverables will include the creation of detailed validation reports and other documentation such as: presentations, detailed memos, development documentation for benchmark or challenger models, and/or other written communications outlining the rationale for MRM outcomes.
• Able to retrieve, analyze and interpret data from various sources (internal and/or external), and transform data (structured or non-structured) appropriately for its use-case.
• Aggregates data and creates datasets from different databases to facilitate statistical analyses.
• Performs ad hoc analyses as needed for review and assessment of considered methods.
• Can interpret the observations and outcomes of statistical analyses performed for communication to senior executive level management in written and verbal form.
• Reads, understands, and interprets regulatory rules and guidance related to the models under development and/or being reviewed/validated.
• Able to understand the product or structure to ensure models capture key business elements and risks.
• Flexible to use various programming languages to identify, investigate and resolve data and programming issues.
• Ability to build strong relationships with stakeholders, business line partners, and colleagues across the Bank.

Basic Qualifications
– Bachelor’s degree in a quantitative field, and eight or more years of relevant experience
OR
– MA/MS in a quantitative field, and five or more years of related experience
OR
– PhD in a quantitative field, and four or more years of related experience

Preferred Skills/Experience

• Experience in Financial Crimes Models (AML or Economic Sanctions) or Compliance (Fair Lending).
• Advanced understanding of applicable compliance laws, regulations, financial services, and regulatory trends that affect assigned line of business.
• Prior exposure to validation or development of BSA/AML models, Fair Lending models, or Artificial Intelligence and/or Machine Learning models within a Financial Institution.
• Deep understanding of Machine Learning and NLP is a plus.
• Experience using Python is highly recommended ; experience using SAS, STATA, R, EVIEWS, or comparable statistical software or languages (e.g., SQL) also desirable.
• Strong people leadership skills.

NOTE: This role offers a hybrid/flexible schedule, which means there’s an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.

If there’s anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to our disability accommodations for applicants .

Benefits:

Our approach to benefits and total rewards considers our team members’ whole selves and what may be needed to thrive in and outside work. That’s why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following (some may vary based on role, location or hours):

• 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

EEO is the Law

U.S. Bank is an equal opportunity employer committed to creating a diverse workforce. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, among other factors. Applicants can learn more about the company’s status as an equal opportunity employer by viewing the federal KNOW YOUR RIGHTS EEO poster.

E-Verify

U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories. The E-Verify program is an Internet-based employment eligibility verification system operated by the U.S. Citizenship and Immigration Services. Learn more about the E-Verify program .

The salary range reflects figures based on the primary location, which is listed first. The actual range for the role may differ based on the location of the role. In addition to salary, U.S. Bank offers a comprehensive benefits package, including incentive and recognition programs, equity stock purchase 401(k) contribution and pension (all benefits are subject to eligibility requirements). Pay Range: $116,280.00 – $136,800.00 – $150,480.00

U.S. Bank will consider qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance.

Job postings typically remain open for approximately 20 days of the posting date listed above, however the job posting may be closed earlier should it be determined the position is no longer required due to business need. Job postings in areas with a high volume of applicants, such as customer service, contact center, and Financial Crimes investigations, remain open for approximately 5 days of the posting listed date.