Risk Actuary - Financial and Model Risk

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.

We are seeking a highly skilled Life Risk Actuary specializing in Financial and Model Risk to join our dynamic team. The ideal candidate will hold either an Associateship (ASA) or Fellowship (FSA) from the Society of Actuaries, showcasing a actuarial background and proven proficiency in developing and leading life actuarial models. Essential to this role is substantial experience in the life actuarial domain, particularly with a keen focus on financial risks associated with health products, especially Medicare Supplement offerings.

This position is essential for safeguarding the integrity of our modeling practices, ensuring adherence to regulatory frameworks, and navigating the complexities of financial risk. The successful candidate will play a pivotal role in improving our actuarial capabilities and contributing to the strategic direction of our organization, thus driving innovation and compliance in a fast-evolving landscape.

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, Phoenix, AZ, Charlotte, NC, or Tampa, FL.

Relocation assistance is not available for this position.

• Performs independent model validation control activities for high risk in-house and vendor models.
• Demonstrates technical approaches to develop and implement validation testing plans.
• Replicates model development and may develop challenger models through predictive modeling, machine learning, deep learning, time-series modeling/forecasting, stress testing, heuristic models, actuarial models, simulation, optimization, and/or other highly niche techniques.
• Conducts and develops plans for model testing and data quality assessments for models using various types of datasets including those employing large datasets and unstructured datasets.
• Reviews at an extensive experience 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.
• Assesses model inherent risk ratings, model declassifications applications, the materiality of model changes, and conducts model change validations for all types models. Coordinates and advises the model validation work of peers.
• Produces and delivers validation reports and related validation work to model validation management, model partners, senior leadership, and others.
• Implements the independent model validation process aligned with the written risk and compliance policies and procedures at an extensive experience level. Evaluates model risk control strengths around model development, implementation, and use. Develops on emerging modeling techniques and approaches.

• 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.
• 6 years of related work experience in model validation, model development, statistical analysis, and/or advanced quantitative research.
• 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 4 years of related work experience in model validation, model development, statistical analysis, and/or advanced quantitative research.
• Experience driving communication verbally and in writing quantitative/technical concepts and conclusions to non-technical audiences, 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. Extensive Experience with at least three 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…