Vice President, Model Risk Management AI, Wealth and Investments

In this role, you’ll make an impact in the following ways: Serves as a senior individual contributor within the Risk & Regulatory Compliance function, specializing in Model Risk Management. Applies advanced, multidisciplinary expertise in financial markets, applied mathematics, statistics, econometrics and computer science to identify, measure and manage risks arising from the development, implementation and use of complex models across BNY. Plays a key role in protecting the firm from potential monetary loss, reputational damage and regulatory censure by independently challenging model design, performance and governance. This role advances BNY’s strategic pillars by strengthening the resilience and integrity of core risk and decision‑making frameworks that underpin client offerings and critical services. It reinforces our Principles by fostering a strong risk culture, advocating for transparency in model assumptions and limitations, and promoting accountable decision‑making grounded in rigorous quantitative analysis and sound governance. Operating within the Model Risk Management job family, the role partners closely with model owners, developers, users and risk stakeholders to ensure models are conceptually sound, empirically robust, properly controlled and used within approved risk appetite. Lead independent model validation and ongoing performance review of complex and/or high‑impact models (e.g., pricing, risk, capital, liquidity, credit, market, treasury, stress testing) by applying advanced quantitative methodologies, back‑testing, benchmarking and sensitivity/robustness analysis to assess conceptual soundness and model performance. Identify, quantify and clearly articulate model risk, limitations and weaknesses by critically reviewing model design, assumptions, data, implementation and use, and documenting findings, recommendations and conditions of use in high‑quality validation reports that withstand internal and regulatory scrutiny. Provide effective second‑line challenge to model developers, model owners and model users by engaging in structured technical dialogue, reviewing remediation plans, and evaluating proposed model changes or new models, ensuring alignment with BNY’s model risk management framework, policies and regulatory expectations. Strengthen model governance and control frameworks by contributing to model inventory accuracy, risk tiering, periodic review cycles, and model risk appetite metrics, while supporting the design and implementation of consistent standards, procedures, and templates across the Model Risk Management function. Support regulatory and internal audit engagements related to model risk by preparing clear, evidence‑based materials, responding to technical inquiries, and addressing issues in a timely and transparent manner, thereby reinforcing trust in BNY’s risk management capabilities. Mentor and provide technical guidance to less experienced team members by reviewing their analytical work, sharing best practices, and promoting a culture of rigorous quantitative discipline, collaboration and continuous improvement within the Model Risk Management community. This role will be focused on GenAI and Wealth Models. To be successful in this role, we’re seeking the following: Advanced degree (Master’s or PhD preferred) in a quantitative discipline such as Mathematics, Statistics, Econometrics, Finance/Financial Engineering, Physics, Computer Science, or related field. Strong grounding in probability theory, statistical inference, time‑series analysis, and/or numerical methods. Professional certifications in risk management or quantitative finance (e.g., FRM, PRM, CQF) beneficial but not required. Typically 5-8 years of experience Advanced quantitative and analytical skills, including hands‑on experience with model development or validation, and proficiency in relevant programming/analytics tools (e.g., Python, R, MATLAB, SAS, or similar). Deep understanding of financial products, risk measurement concepts and regulatory expectations related to model risk, with the ability to translate complex technical issues into clear risk narratives and recommendations. Strong communication and stakeholder‑management skills, with the ability to provide credible challenge, influence decision‑makers, and produce high‑quality written documentation suitable for senior management, regulators and auditors.