Join EY GDS Assurance Digital and drive impactful product development through innovative AI research. This role involves creating analytics-enabled solutions and integrating data science with business needs to extract valuable insights from data. You will collaborate with diverse, multi-disciplinary teams to support global clients, blending technical expertise with business development in AI to solve complex business challenges and steer innovation agendas.

Spearhead AI Governance initiatives, focusing on Responsible AI, model governance, explainability, transparency, fairness, accountability, and monitoring. Define robust governance controls for Generative AI, Agentic AI, Machine Learning, and Advanced Analytics. Collaborate with business stakeholders, technology teams, risk, compliance, legal, and security functions to establish governance requirements for data and AI projects. Design and implement data quality frameworks, controls, and remediation processes. Ensure compliance with internal policies and regulatory mandates by working closely with data, analytics, and AI teams. Conduct governance maturity assessments and develop roadmaps for ongoing improvement, while supporting audit, risk, and regulatory activities. Create governance metrics, dashboards, and executive reports, and lead governance councils and working groups. Build and mentor high-performing governance teams, promoting best practices across the organization.

A minimum of 12-17 years of experience in AI Governance is essential, encompassing Responsible AI frameworks, AI risk management, and model governance. Expertise in regulatory and compliance knowledge, including DPDPA, Model Risk Management Frameworks, and internal audit requirements, is crucial. A strong understanding of the Machine Learning lifecycle, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, OpenAI, and Azure OpenAI Services, as well as AI security and governance controls, is expected. Candidates should possess excellent academic credentials, including at least a Bachelor's or Master's degree in a relevant field like Computer Science, Information Systems, Data Science, Engineering, Business Analytics, Statistics, or Risk Management. Proven experience in implementing enterprise-wide governance programs and operating models is a key requirement.