Model Validator Senior

USAA•Tampa, FL

3d•Hybrid

About The Position

As a dedicated Model Validator, you will execute model risk validation oversight for the life-cycle management of models which includes conducting model validation activities. The incumbent will execute 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 stakeholders) throughout the lifecycle of the model's use and maintenance. 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.

Requirements

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; 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 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 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.

Nice To Haves

Experience with common modeling program languages such as SAS or Python
Experience developing and/or validating models using common econometric modeling techniques such as logistic regression, ols, and time series methods.
Experience developing and/or validating machine learning and/or artificial intelligence (AI/ML) models
Experience working with common bank modeling exercises such as stress testing, reserving, asset/liability management, deposit forecasting, pricing, or credit origination.
Strong interpersonal and written communication skills
Post-graduate degree in a quantitative field.

Responsibilities

Executes independent model validation control activities for high risk in-house and vendor models.
Leverages expert technical approaches to develop and execute 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 specialized techniques.
Conducts and develops plans for model testing and data quality assessments for models using various types of datasets including those leveraging 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 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.
Oversees and advises the model validation work of peers.
Produces and delivers validation reports and related validation work to model validation management, model stakeholders, senior leadership, and others.
Executes the independent model validation process compliant 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.
Professionally develops on emerging modeling techniques and approaches.