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 Modeling and Machine Learning Analyst Senior for any of our office locations. This position is a hybrid work type and can be based in one of the following locations: San Antonio, TX; Plano, TX; Phoenix, AZ; Charlotte, NC; Colorado Springs, CO or Tampa, FL. Hybrid roles help employees gain the best of both worlds – collaborating in-person in the office and working from home when needed to achieve focused results.
The Opportunity
What you’ll do:
The Credit Risk Modeling team is looking for a Modeling and Machine Learning Analyst to work on development and maintenance of advanced systems of statistical and machine learning models.
Develops, reviews, and / or implements various types of models. Leverages advanced modeling and machine learning techniques to solve important business problems. Communicates insights and business impact of model-based solutions to stakeholders.
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 best practices in model risk.
- Identifies and manages existing and emerging risks that stem from business activities and the job role.
- Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled.
- Follows written risk and compliance policies, standards, and procedures for business activities.
- Develops, reviews, or implements major model components for various types of models.
- Identifies or reviews model-based business solutions to improve Business strategies.
- Communicates modeling insights to technical and non-technical audiences and stakeholders.
- Conducts model development and/or review efforts utilizing modeling and machine learning 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 ideate, and / or review powerful and high- quality data features for modeling and machine learning.
- Leverages broad technology stack that includes Python, R, or SAS to develop or evaluate modeling or machine learning solution.
- Builds for the future by conducting research on latest machine learning techniques, large-scale computing, automation or best practices in model risk. Educates modeling and data science community on findings.
- Maintains, creates, and/or reviews automation tools and repeatable code base, designed to promote reproducible research, and to reduce operational risks and costs to the organization.
- Creates or reviews model-based solutions and accompanying technical documentation consistent with regulatory requirements and works with other lines of defense as needed.
- Conducts and/or reviews development and automation of performance monitoring 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 discipline experience beyond the minimum required may be substituted in lieu of a bachelor’s degree.
- 6 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 4 years of related work experience in predictive modeling, model governance, machine learning or large data analysis.
- Proficiency 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 best practices in using modeling and machine learning techniques and methods to solve business problems.
- Proficiency in developing or reviewing modeling solutions based on Python, R, SAS or other technology stack.
- Demonstrated ability to write technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences.
What sets you apart:
- Experience with credit risk loss forecasting, reserving, stress-testing models, balance prediction models, and prepayment modeling across various retail books of business
- Ability to work across several statistical/coding systems, such as SAS, R and Python, at once
- Hands-on experience with Model Risk Management requirements and practices
- Experience with creation of complex model-related documentation, such as development documentation, validation reports, on-going monitoring reports
- Excellent writing 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: $ 104,660 – $ 199,970.
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.