Senior Lead - Model Validation

Role Overview

The Senior Lead in Model Validation is charged with independently verifying both quantitative and qualitative models employed across the bank. This leadership position entails steering a team dedicated to evaluating model integrity, adhering strictly to internal and regulatory validation policies, and fostering resilient risk management protocols.

Key Duties and Responsibilities

• Designing, updating, and enforcing the Model Validation Policy, framework, and standards to align with the bank's risk appetite and meet regulatory expectations.
• Overseeing full-cycle model validation processes to guarantee models function as intended, providing independent oversight across the enterprise.
• Acting as the central liaison for internal audits and regulatory exams related to model validation efforts.
• Administering quality assurance processes such as peer reviews and consistency checks to uphold superior validation practices.
• Leading and developing a multidisciplinary validation team managing diverse model types, including those related to risk, investment, fraud, compliance, finance, HR, as well as emerging Gen AI and agentic applications.
• Delivering clear validation reports addressing key risks, uncertainties, corrective actions, and evolving trends, and facilitating their approval through relevant risk committees.
• Maintaining and innovating validation methodologies, ensuring thorough evaluations of model design, data, implementation, and performance, especially for advanced models like LLM-enabled systems.
• Managing relationships with regulators, auditors, and senior management, effectively communicating validation insights and risk implications.

Required Expertise and Technical Knowledge

• Extensive experience with a wide array of models, including Machine Learning and Large Language Models.
• Deep understanding of model risk management principles and regulatory frameworks such as SR26-2 and SS1/23, with proven engagement experience with regulators and internal audit teams.
• Technical proficiency in programming and analytical tools such as Python, SAS, R, or C++, with awareness of AI governance and contemporary model validation methodologies.
• Exceptional ability to simplify and communicate complex technical issues to executives and regulatory authorities.
• Highly analytical mindset with strong problem-solving capabilities, able to handle challenging situations and tight deadlines both independently and collaboratively.
• Excellent verbal and written communication skills for presentations to senior committees, executives, and regulatory bodies.
• Strong organizational skills that enable effective management of multiple priorities under pressure.

Qualifications and Experience

• Advanced degree (Master’s or Ph.D.) in a quantitative discipline such as Mathematics, Statistics, Finance, Data Science, Financial Engineering, Computer Science, or Economics.
• 8 to 10 years of pertinent experience in model validation, risk management, and development, including a minimum of 5 years leading layered model validation teams.
• Fluency in English at an advanced level.