U.S. Bank Model Risk Specialist - Multiple Locations in Charlotte, North Carolina
At U.S. Bank, we're passionate about helping customers and the communities where we live and work. The fifth-largest bank in the United States, we’re one of the country's most respected, innovative and successful financial institutions. 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.
Job DescriptionU.S. Bank is looking for a Model Risk Specialist to join the Chief Digital Office (CDO) Risk Team, as we build out our risk oversight program.
At U. S. Bank, we want to satisfy our customers' financial needs and help them succeed financially. We're looking for talented people who will put our customers at the center of everything we do. Join our diverse and inclusive team where you'll feel inspired to contribute your unique skills and experience.
The Digital Risk group works with our Digital Platforms Teams to identify and manage risk.
The group works with several enterprise risk groups, including regulatory compliance, credit, financial crimes, information security, model, operational and technology risk.
The Model Risk Specialist is a hands-on role that will be primarily responsible for providing first line of defense risk reviews of models, ongoing oversight of existing models as well as new models working with the enterprise risk processes and regulatory compliance requirements.
This role will work within the fast-paced CDO team, which strives for excellence in all phases of execution and lifecycle management.
The ideal candidate will have the right attitude and an imaginative mind set, great problem-solving skills, is creative, and has extensive experience with AI/ML and Model Risk solution delivery within industry.
This Model Risk Specialist supports the CDO function by: The individual will be comfortable evaluating emerging business line solutions and technologies to assess model risk within the existing MRM risk environment. Collaborating with business lines, model owners, and model validation to ensure MRM program requirements are understood and used accurately. Creating model documentation; includes working with internal and external model owners, creating monitoring reports and plan as requested by MRM policies, and implementation documentation, for completeness against program standards and templates. Regularly working with model owners monitoring existing models to ensure compliance with MRM program requirements. Regularly meeting with the model owners and validators to discuss new models, model changes, redevelopments or retirements, and current model issues. Assesses risk associated with AI/ML solutions, both during experimentation and in preparation for deployment to production within the enterprise. Execute various regression techniques, parametric and non-parametric algorithms, times series techniques, and other statistical models, various model validation tests/methodologies, using SAS and/or Python or similar statistical packages. Analyzes and comprehends Federal and state regulatory requirements, in collaboration with the Business, Legal, Risk, and Compliance groups, as they pertain to model risk. Provides risk-related insights to the other Product and Enterprise teams as part of the accelerated incubation of new capabilities. Thinking critically about continuous process improvements. Maintains current knowledge of the model building (AI/ML) technology landscape and emerging developments.
- Bachelor's degree, or equivalent work experience
- Ten or more years of experience in an applicable risk management environment
- Applicable certifications
- Master's degree in a quantitative STEM field (e.g., Physics, Mathematics, Computer Science, Operations Research, Statistics, or related quantitative/technical field) or at least 2 years of experience in both AI/ML technology applications and risk assessment processes.
- At least six years of statistical modeling experience within the financial services industry.
- Extensive experience with risk assessments in an industry setting within a large organization (banking/finance industry preferred).
- Applicable certifications in SAS or Python or R or SQL, etc.
- Excellent written, verbal, and presentation communication skills, including the ability to effectively communicate MRM program requirements to persons or business lines previously unfamiliar with the requirements.
- Experience with Federal and state regulations pertaining to model risk management in the financial/banking industry.
- Advanced understanding of applicable laws, regulations, financial services, and regulatory trends that affect assigned line of business.
- Knowledge/familiarity with a broad range of AI/ML algorithms.
- Familiarity with database design principles and data access methods.
- Knowledge of programming and software design fundamentals, object oriented and functional design principles, best practices, etc.
- Experience delivering communications in a clear, concise, and compelling manner.
Benefits: Take care of yourself and your family with U.S. Bank employee benefits. We know that healthy employees are happy employees, and we believe that work/life balance should be easy to achieve. That's why we share the cost of benefits and offer a variety of programs, resources and support you need to bring your full self to work and stay present and committed to the people who matter most - your family.
Learn all about U.S. Bank employee benefits, including tuition reimbursement, retirement plans and more, by visiting usbank.com/careers.
EEO is the Law Applicants can learn more about the company’s status as an equal opportunity employer by viewing the federal EEO is the Law poster.
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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.