Advanced Analytics and AI Lead

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization’s next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential FunctionsTalent Intelligence Strategy & Executive Advisory • Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. • Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. • Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc • Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. • Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions • Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. • Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. • Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. • Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. • Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions • Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. • Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. • Build conversational analytics experiences that enable leaders to interact with talent data through natural language. • Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. • Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. • Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership • Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. • Lead development of enterprise Talent data products designed for broad organizational consumption. • Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. • Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. • Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. • Enable scalable analytics architecture supporting structured and unstructured talent data. • Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. • Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications • Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. • Create executive dashboards and insight products that simplify complex workforce information. • Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. • Present findings confidently to executive talent leaders and senior business stakeholders. • Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development • Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. • Establish talent intelligence standards, methodologies, and governance frameworks. • Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. • Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. • Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities • Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. • Prioritize investments and resource allocation across analytics, AI, and data product portfolios. • Define and monitor key workforce intelligence metrics and success measures. • Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. • Balance innovation investments with operational scalability, governance, and business value realization. • Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills RequirementsStrategic & Business Skills • Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. • Strong consulting, stakeholder management, and executive influence capabilities. • Ability to align talent analytics outcomes with broader business objectives. • Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills • Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills • Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills • Data Bricks, Microsoft Fabric, Power BI and advanced visualization. • SQL and advanced data modelling. • Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning • Python and R, Modern cloud analytics architectures. • API and data integration concepts, Data governance and metadata management. Leadership Competencies • Executive presence, Strategic thinking, Innovation mindset, Change leadership. • Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. • Ability to cope with ambiguity; to drive c