VP, Model Validation

VP, Model Validation

The VP, Model Validation is within Synchrony Model Risk Management function and is responsible for leading a model validation team of quantitative analysis, focusing on the validation of Finance & Treasury, Anti-Money Laundering, consumer banking, and marketing models and ensuring the compliance with regulatory guidelines as well as Model Risk Management policies, standards, and procedures.

Essential responsibilities include overseeing the entire Finance & Treasury and Anti-Money Laundering model risk management process, ensuring compliance with MRM policies and controls; leading and directing in the validation of models, including full review scopes, annual assessments, and ongoing monitoring; assuming complete responsibility for the quality of validations, managing timelines, and ensuring project completion aligns with regulatory guidelines; maintaining current knowledge of the latest advancements in model development and validation practices; representing the MRM in discussions with regulators, senior management, and during internal audits; working collaboratively with various teams across Synchrony to uncover, highlight, and identify model risk associated with models; and serving as model risk expert in various groups including MRM working group and Model Risk Oversight Committee.

Qualifications / requirements include a master's degree and 12+ years' experience in model development / model validation in a US large retail bank or a bachelor's degree and 15+ years' experience in model development / model validation in a US large retail bank or a high school diploma and bachelor's degree and 19+ years' experience in model development / model validation in a US large retail bank; proven experience in leading model validation efforts in a large bank, particularly in Finance & Treasury including ALM, Liquidity, Pricing, PPNR, etc. and Anti-Money Laundering, with a strong background in machine learning and GEN AI models; demonstrated ability to navigate and comply with regulatory requirements and guidelines; strong leadership skills with the ability to manage and direct a high performing team; excellent communication and collaboration skills, with experience in liaising with regulators, senior management, and cross functional teams; deep understanding of model risk management frameworks and the ability to drive improvements and best practice within the organization; thorough business knowledge and sharp acumen in loss forecasting with comprehensive understanding and strategic insight supporting ACL (Allowance for Credit Losses) and financial / capital planning; and strong programming skills with 6+ years' hands-on and proven experience utilizing Python, Spark, SAS, SQL, AWS, Data Lake to perform statistical analysis and manage complex or large amounts of data.

Desired characteristics include a master's degree (or foreign equivalent) in Statistics, Mathematics preferred; advanced knowledge of regulatory requirements for Model Risk Management; 12+ years of experience in credit loss modeling in areas such as Loss Forecasting, Allowance, Stress Testing, or other areas with consumer credit estimation methodologies; experience with multiple credit loss methodologies such as PD / EAD, vintage, roll rates, etc.; experience in anti-money laundering models; solid knowledge in machine learning model techniques; proven experience in people and project management; excellent written and oral communication and presentation skills; and legal authorization to work in the U.S.