Advanced Analytics and AI Lead

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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 Functions:
Talent Intelligence Strategy & Executive Advisory

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• 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

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• 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

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• 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

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• 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