Why USAA?
Let’s do something that really matters.
At USAA, we have an important mission: facilitating the financial security of millions of U.S. military members and their families. Not all of our employees served in our nation’s military, but we all share in the mission to give back to those who did. We’re working as one to build a great experience and make a real impact for our members.
We believe in our core values of honesty, integrity, loyalty and service. They’re what guides everything we do – from how we treat our members to how we treat each other. Come be a part of what makes us so special!
We are seeking a dedicated Model Risk Governance Lead for any of the following office locations: San Antonio, TX; Plano, TX; Phoenix, AZ; Charlotte, NC; Colorado Springs, CO or Tampa, FL.
The Opportunity
The Model Risk Governance Lead will play a central role in creating and maintaining the USAA Bank Risk Governance framework for models consistent with business and regulatory requirements. Assist the Bank Model Governance Committee in meeting model risk oversight requirements. Collaborate with senior management and colleagues in business and staff functions, independent risk management, legal and compliance in leading the annual process to revise model risk policies, procedures, and standards. Perform subject matter authority reviews of models to ensure they meet model risk management requirements. Handle monitoring of model risk policy requirements and related metrics and escalate breaches. Design and deliver training to partners on policies, procedures, standards, and systems.
Leads the development, review, and / or implementation of entire model lifecycle. Leverages advanced modeling and machine learning techniques to solve important business problems. Communicates insights and business impact of model-based solutions to partners. Keeps models well managed and aligned with USAA model risk policy and regulatory expectations. Builds tools or capabilities for the future by researching powerful new data sources, latest algorithms or standard processes in model risk.
What you’ll do:
- Identifies and leads existing and emerging risks that stem from business activities and the job role.
- Ensures risks associated with business activities are effectively identified, measured, supervised, and controlled.
- Follows written risk and compliance policies, standards, and procedures for business activities.
- Leads development and/ or review of entire lifecycle of the modeling and machine learning project, leads projects, serves as a subject matter authority, and as a mentor to others.
- Partners with business leaders to identify needs for model-based solutions, assists in developing business requirements for model development and measures for success.
- Communicates modeling insights to technical and non-technical audiences and senior partners across the organization.
- Uses modeling and machine techniques such as linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, various simulation methods, or other advanced techniques to solve important business problems.
- Partners with business and data teams to conceptualize, obtain and / or review powerful and high-quality data features for modeling and machine learning.
- Demonstrates broad technology stack that includes Python, R, or SAS to develop or evaluate modeling or machine learning solution.
- Builds for future by conducting research on latest machine learning techniques, large-scale computing, automation or standard processes in model risk. Educates modeling and data science community across organization on findings.
- Mentors and provides consultation to team members and peers. Leads and guides team members in model data, model development, techniques, and methods. Coaches and shares findings on machine learning and application to enterprise models.
- Maintains, builds, or reviews automation tools and repeatable code base, crafted to promote reproducible research, and to reduce operational risks and costs to the organization.
- Builds or reviews model-based solutions and accompanying technical documentation consistent with regulatory requirements, working with other lines of defense as needed.
- Leads and/or reviews development and automation of performance supervising tools to maintain modeling and machine learning solutions.
What you have:
- Bachelor’s degree in a quantitative field, such as Mathematics, Statistics, Data Science, Computer Science, or a related quantitative STEM field (Science, Technology, Engineering, and Math). Four additional years of related quantitative subject area experience beyond the minimum required may be substituted in lieu of a bachelor’s degree.
- 8 years in predictive modeling, model governance, machine learning or large data analysis. OR Advanced Degree (e.g., Master’s, PhD) in quantitative field, such as Mathematics, Statistics, Data Science, Computer Science, OR a Related quantitative STEM field (Science, Technology, Engineering, and Math) and 6 years of related work experience in predictive modeling, model governance, machine learning or large data analysis.
- Expert in developing or reviewing modeling solutions based on broad range of modeling and machine learning techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
- Demonstrated ability to apply standard processes in using modeling and machine learning techniques to proactively identify and solve business problems.
- Expert in developing or reviewing modeling solutions based on Python, R, SAS or other technology stack.
- Proven ability to write and edit complex technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences.
What sets you apart:
- The ideal candidate will have a validated ability to build and maintain a control, governance, or oversight framework and ability to gain consensus by resolving input from diverse partners
- Strong understanding of Bank regulatory requirements for modeling and model risk management lifecycle and processes
- Experience analyzing complex quantitative models and the risks and controls around their usage, including artificial intelligence and machine learning models
- Ability to clearly communicate and present ideas and concepts with senior leadership and other partners
- Strong critical thinking and problem-solving skills
The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.
What we offer:
Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. The salary range for this position is: $ 115,240 – $ 220,270.
Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.
Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.
For more details on our outstanding benefits, please visit our benefits page on USAAjobs.com.
Relocation assistance is not available for this position.
USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.