Set enterprise direction for model validation—delivering independent, risk-based oversight across a diverse portfolio of models spanning investment and risk management, fraud and compliance, finance and HR, and rapidly evolving Gen AI and agentic use cases
Serve as the senior authority for model validation, setting the bar for defensible methodologies, rigorous challenge, and clear, decision-ready risk communication to senior leaders
Strengthen model risk culture and lifecycle discipline across the enterprise—driving timely issue remediation, elevating validation quality and consistency, and ensuring practices remain aligned with regulatory and audit expectations
Lead a high‑performing, multidisciplinary model validation team responsible for validating a diverse portfolio of models
Serve as the final approval authority for validation reports on higher-risk models
Oversee adherence to enterprise model lifecycle requirements—including model inventory accuracy, change management, ongoing monitoring, and issue remediation
Own the enterprise’s model development and model validation standards, guidelines, procedures, and templates
Deliver clear, actionable reporting on key model risks, model uncertainty, issue remediation, and emerging trends to senior committees and executives
Support the development and enhancement of divisional and enterprise model‑quality scorecards
Requirements
Advanced degree in technical field (e.g. Master's or doctoral degree in quantitative discipline such as Mathematics, Statistics, or Economics)
10+ years of experience across model development, model validation, and model risk management, including a minimum of five years leading multi-layered model validation teams
Extensive experience with a broad range of model types, including machine learning/LLM-based models
Deep knowledge of model-risk management principles and regulatory frameworks (e.g., SR26-2, SS1/23) and demonstrated experience engaging with regulators and internal audit
Strong technical proficiency with programming languages and analytical tools such as Python, R, or C++
Proven ability to translate complex technical concepts into clear, actionable insights for senior executives
Exceptional written and verbal communication skills, including experience presenting to senior committees, executives, and regulatory bodies
Demonstrated ability to partner with stakeholders to balance effective challenge, practical solutions, and business objectives