Head of Validation, Model Risk Management

Location: Malvern

Overview

The Head of Validation, Model Risk is a senior leadership role responsible for setting 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. This role serves as the senior authority for model validation, setting the bar for defensible methodologies, rigorous challenge, and clear, decision-ready risk communication to senior leaders.

The Head of Validation will strengthen model risk culture and lifecycle discipline across the enterprise-driving timely issue remediation, elevating validation quality and consistency, and ensuring Vanguard's practices remain aligned with regulatory and audit expectations.

Responsibilities

Leadership & Team Management

* Leads a high‑performing, multidisciplinary model validation team responsible for validating a diverse portfolio of models including investment and risk management, fraud and compliance, finance and HR, as well as Gen AI and Agentic use cases

* Develop and mentor talent to promote strong technical capabilities and a high-quality validation process

Validation Oversight & Approval

* Serve as the final approval authority for validation reports on higher-risk models

* Ensure validation conclusions are robust, well‑supported, and communicated clearly to stakeholders with varying levels of technical expertise

Model Risk Governance & Lifecycle Management

* Oversee adherence to enterprise model lifecycle requirements-including model inventory accuracy, change management, ongoing monitoring, and issue remediation.

* Drive timely resolution of model‑related issues and non‑compliance, escalating when necessary

* Strengthen model‑risk culture across the enterprise through targeted training, outreach, and proactive engagement with model owners and developers

Methodology & Practice Leadership

* Define, maintain, and continually enhance the methodologies and test approaches used in model validation

* Ensure comprehensive assessment of conceptual soundness, performance, data quality, implementation accuracy, and other model risk considerations

* Lead the evolution of validation techniques for emerging modeling approaches, including LLM‑enabled and agentic systems

Standards, Policies & Quality Assurance

* Own the enterprise's model development and model validation standards, guidelines, procedures, and templates.

* Establish and oversee quality assurance mechanisms-including peer review, thematic reviews, and consistency checks-to ensure embedment of high-quality validation practices.

Executive Reporting & Model Risk Insights

* 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 and contribute to the risk‑appetite process

Senior Stakeholder, Regulatory & Audit Engagement

* Serve as a primary point of contact for regulators, internal audit, and senior leaders on model validation related matters

* Articulate validation rationales, modeling assumptions, and risk implications clearly and confidently to supervisory authorities and executive stakeholders.

Qualifications

* 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++, and familiarity with emerging technologies, AI governance, and modern model development practices.

* Proven ability to translate complex…