SVP - Model Risk Management AI, Wealth and Investments

Bank of New York Mellon•New York, NY

3d•$104,000 - $200,000•Onsite

About The Position

We’re seeking a future team member for the role of SVP - Model Risk Management AI, Wealth and Investment to join our Model Risk team. This role is located in New York City, New York. In this role, you’ll make an impact in the following ways: Lead the Model Risk Management framework for a defined portfolio of models (e.g., pricing, risk, capital, stress testing, AI/ML, and valuation models) by setting clear standards for model risk identification, assessment, validation and governance, and by ensuring consistent application across businesses and legal entities. Oversee and review independent model validations and ongoing performance monitoring by demonstrating deep quantitative expertise, providing effective challenge to model design, data, assumptions and implementation, and ensuring that model risk is appropriately quantified, documented and mitigated. Establish and chair or actively contribute to model risk governance forums by defining decision‑making processes, setting model approval thresholds and ensuring that model risk topics are escalated, debated and resolved in line with internal policies and regulatory expectations. Advise senior business, risk and Engineering stakeholders on model risk issues and emerging quantitative methodologies by translating complex analytical concepts into clear risk insights and recommendations that support sound business decisions and responsible innovation. Drive continuous enhancement of the firm’s model risk policies, standards, tools and methodologies by monitoring external regulatory developments, industry good practice and advances in quantitative methods, and by embedding these into practical, risk‑sensitive processes. Manage, develop and coach a team of model risk professionals by setting clear objectives, providing technical and behavioral guidance, promoting a culture of rigorous challenge and collaboration, and ensuring appropriate capacity and capabilities to meet current and emerging model risk demands. This role will be focused on GenAI and Wealth Models.

Requirements

Advanced degree (Master’s or PhD preferred) in a quantitative field such as mathematics, statistics, econometrics, physics, engineering, quantitative finance or computer science, or equivalent experience.
Professional certifications in risk, quantitative finance or related areas (e.g., FRM, PRM, CQF) are advantageous.
Strong knowledge of financial markets, products and risk management practices, including experience with complex mathematical/statistical modeling techniques.
Typically, 8-12 years of experience
Advanced quantitative and analytical skills, including deep knowledge of model development, validation and performance measurement techniques, and the ability to provide credible effective challenge.
Strong leadership, communication and stakeholder management skills, with the ability to influence senior leaders, shape governance decisions and translate complex quantitative issues into clear risk insights.
Proven people management capabilities, including building and leading high‑performing quantitative teams, coaching technical staff and fostering a culture of integrity, accountability and continuous improvement in risk management.

Nice To Haves

Professional certifications in risk, quantitative finance or related areas (e.g., FRM, PRM, CQF) are advantageous.

Responsibilities

Lead the Model Risk Management framework for a defined portfolio of models (e.g., pricing, risk, capital, stress testing, AI/ML, and valuation models) by setting clear standards for model risk identification, assessment, validation and governance, and by ensuring consistent application across businesses and legal entities.
Oversee and review independent model validations and ongoing performance monitoring by demonstrating deep quantitative expertise, providing effective challenge to model design, data, assumptions and implementation, and ensuring that model risk is appropriately quantified, documented and mitigated.
Establish and chair or actively contribute to model risk governance forums by defining decision‑making processes, setting model approval thresholds and ensuring that model risk topics are escalated, debated and resolved in line with internal policies and regulatory expectations.
Advise senior business, risk and Engineering stakeholders on model risk issues and emerging quantitative methodologies by translating complex analytical concepts into clear risk insights and recommendations that support sound business decisions and responsible innovation.
Drive continuous enhancement of the firm’s model risk policies, standards, tools and methodologies by monitoring external regulatory developments, industry good practice and advances in quantitative methods, and by embedding these into practical, risk‑sensitive processes.
Manage, develop and coach a team of model risk professionals by setting clear objectives, providing technical and behavioral guidance, promoting a culture of rigorous challenge and collaboration, and ensuring appropriate capacity and capabilities to meet current and emerging model risk demands.