Model Validator Lead-(AML/Fraud)

Why USAA?

At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.

Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. Be part of what truly makes us special and impactful.

The Opportunity

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position.

Executes model risk validation oversight for the life-cycle management of models for high risk and highly complex models. Executes the model validation oversight process compliant with the written risk and compliance policies and procedures which require independence from model stewards (e.g., model owners, developers, implementers, users, and other collaborators) throughout the lifecycle of the model's use and maintenance.

What you'll do:

• Oversees and conducts independent model validation control activities for high visibility, critical and/or specialized models. Uses expert business and technical model and model validation knowledge to conduct highly specialized validation activities for models that leverage groundbreaking techniques that require specialized credentials, and models that have higher enterprise visibility and risk.
• Leverages specialized technical approaches to develop, implement, and execute validation testing plans for models that require experienced model validation knowledge and skills.
• Leads the team in developing challenger models and/or replicating model development through predictive modeling, machine learning, deep learning, time-series modeling/forecasting, stress testing, heuristic models, actuarial models, simulation, optimization, and/or other techniques including models that require specialized skills.
• Develops plans, reviews peers' plans and provides feedback on model tests and data quality assessments for models using various types of datasets including those demonstrating large datasets and unstructured datasets.
• Reviews at a subject matter authority level the end-to-end life-cycle management of model development, implementation, ongoing monitoring, and use in areas of Banking and Insurance (Property & Casualty and Life) along with their corresponding business support functions and operational processes.
• Responsible for assessing model inherent risk ratings, model declassifications applications, materiality of model changes, and other reviews of models as part of model validation-related governance processes.
• Produces and delivers validation reports and related validation work to model validation management, model collaborators, senior leadership, and others for high visibility, critical and/or specialized models. Provides review of validation work produced by peers in preparation of report issuance.
• Reports validation results and model risk trends/metrics to EMRM leadership.
• Executes the independent model validation process aligned with the written risk and compliance policies and procedures at a subject matter authority level. Evaluates model risk control strengths around model development, implementation, and use as it pertains to elements of model conceptual soundness, modeling methodology, model limitations, data quality, ongoing monitoring, and other more complex elements of the model validation process.
• Interacts with internal and external peers for awareness and applicability of ground breaking techniques, technologies, and potential business solutions while continuing to professionally develop and knowledge share emerging modeling techniques and approaches

What you have:

• Bachelor's degree in a quantitative field, such as Economics, Mathematics, Statistics, Actuarial Science, Data Science, Engineering, Computer Science, or a Related Field with Core Quantitative Curriculum. Four additional years of related experience beyond the minimum required may be substituted in lieu of a degree.
• 8 years of related work experience in model validation, model development, statistical analysis, and/or advanced quantitative research

Or

• Advanced degree (e.g., Master's, PhD) in a quantitative field, such as Economics, Mathematics, Statistics, Actuarial Science, Data Science, Engineering, Computer Science, or Related Field with Core Quantitative Curriculum and 6 years of related work experience in model validation, model development, statistical analysis, and/or advanced quantitative research.
• Strong experience communicating complex quantitative/technical concepts and conclusions to senior leadership, auditors, and/or regulators.
• Strong programming skills in R, Python, SAS, Java, C, SQL, and/or other comparable programming languages for the iterative methodological tenants of model and algorithm development including setting model specifications, assumption testing, data quality assessments, variable selection, back-testing, benchmarking, and other robust model testing. Subject Matter Depth and Breadth with at least four of the following statistical, econometric, data science, and predictive modeling approaches: Unsupervised Learning; K-Means; Linear Regression; Time-Series/Forecasting; Stress Testing; Logistic Regression; Gaussian Process; Simulation Models; Boosting/Bagging Trees; Neural Networks; Deep Learning Concepts; Bayesian Estimators.
• Strong business context knowledge in operational and support functions of Banking and/or Insurance as well as associated modeling and analytics knowledge.
• Business and industry skill in modeling governance techniques and approaches.
• Experience sharing modeling governance technical expertise and guidance with peers.

What sets you apart:

• Understanding of Anti-Money Laundering or Fraud models.
• Experience evaluating and challenging complex models and explaining issues in an intuitive way.
• Extensive experience of statistical and machine learning modeling techniques.
• Program/Project management experience with senior leaders.
• Experience with SAS, Python or R.
• US military experience through military service or a military spouse/domestic partner [optional]

Compensation range: The salary range for this position is: $189,370- $361,950.

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.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

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.

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, visit our benefits page on USAAjobs.com.

Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.

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.