At Regions, we believe associates deserve more than just a job. We believe in offering performance-driven individuals a place where they can build a career --- a place to expect more opportunities. If you are focused on results, dedicated to quality, strength and integrity, and possess the drive to succeed, then we are your employer of choice. Regions is dedicated to taking appropriate steps to safeguard and protect private and personally identifiable information you submit. The information that you submit will be collected and reviewed by associates, consultants, and vendors of Regions in order to evaluate your qualifications and experience for job opportunities and will not be used for marketing purposes, sold, or shared outside of Regions unless required by law. Such information will be stored in accordance with regulatory requirements and in conjunction with Regions’ Retention Schedule for a minimum of three years. You may review, modify, or update your information by visiting and logging into the careers section of the system. Job Description: At Regions, the Risk Quantitative Model Validation Analyst serves as a member of a key strategic team that is responsible for performing independent model risk oversight activities, including model identification, determination, classification, inventory management, validation, review, issue remediation testing, reporting, and related activities. The associate will test data products, including models and analytical tools, in the areas of fraud monitoring, cybersecurity, credit scoring, marketing, BSA/AML/OFAC compliance, market risk, capital markets, operational risk, finance and accounting, loan pricing, deposit pricing, loan valuation, and economic capital. In Model Risk Management and Validation (MRMV), the Risk Quantitative Model Validation Analyst works with multiple teams of validation analysts, governance analysts, as well as automation specialists to validate highly complex quantitative models, including Artificial Intelligence (AI) and Machine Learning (ML) approaches. The ideal candidate has knowledge in data management, visualization, automation, quantitative modeling methods and programming skills.