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Overview The Manager, People Analytics & Insights leads the development and delivery of data-driven insights that inform workforce strategy and elevate organizational performance. This role sits at the intersection of HR, business strategy, and data analytics, transforming complex data into clear, actionable recommendations for senior leadership. Reporting to the Director of People Analytics & Insights, the role works with senior HR leaders, COE heads, and business stakeholders to lead complex, often ambiguous analytical workstreams where the method, framing, and recommendation are as important as the data itself. Core Responsibilities Domain Ownership: Sets the analytical agenda of Talent Acquisition and Talent Development, defining relevant metrics, and ensuring outputs are consistently high quality, strategically relevant, and aligned to organizational priorities. Complex & Ambiguous Analysis: Lead end-to-end analysis of complex problems, independently framing the question, selecting or developing the appropriate methodology, and delivering findings that meaningfully shift understanding or decision-making. Stakeholder Influence: Engage senior HR and business stakeholders not just to explain findings, but to shape how they think about problems, influencing approach and direction. Insight Narrative & Recommendations: Develop well-reasoned, evidence-based recommendations. Data Quality & Governance Standards: Take accountability for the integrity and governance of people data within the domain, driving resolution across systems and process owners and contributing to enterprise-wide data standards. Informal Leadership: Provide ongoing coaching and quality review for junior analysts, reviewing outputs, developing analytical capability, and raising team standards through day-to-day collaboration. Innovation & Continuous Improvement: Proactively identify where existing approaches, models, or processes are insufficient and develop new ones, building new analytical capabilities where gaps exist. Benchmarking & External Perspectives: Lead benchmarking and external research initiatives, interpreting comparative data in context and synthesizing external trends into actionable implications for the organization. Skills & Qualifications Essential Experience: 8-12 years of experience in data analytics, people analytics, or a closely related discipline, with demonstrated experience owning analytical domains and driving insight-led decisions at a senior level in complex organizations. Education: Degree-level qualification (or equivalent) in Data Analytics, Statistics, Economics, Organizational Psychology, Human Resources, or a related field. Postgraduate qualification or equivalent depth of practice is an advantage. Technical Depth: Expert proficiency in BI tools (e.g. Power BI, Tableau) and Excel; advanced SQL; strong working proficiency in Python or R, including applying statistical or predictive methods to workforce data. Actively uses AI tools to enhance the quality and efficiency of analytical work. Methodological Range: Able to design as well as apply analytical methods - including regression modelling, clustering, attrition prediction, or scenario modelling - and judge which approach is right for the problem, not just the tool at hand. Framework & Standards Design: Demonstrated ability to design metrics frameworks, define analytical standards, or build scalable reporting infrastructure that others can work to. HR Systems & Data Governance: Deep familiarity with HR data platforms (e.g. Workday, SAP SuccessFactors), data structures, and governance considerations, including multi-country and GDPR complexity. Influence & Communication: Proven ability to shape how senior stakeholders think, not just reporting findings, but persuading, reframing, and leading discussions with credibility and composure under challenge. Autonomy: Consistently works independently on ambiguous, high-stakes problems. Comfortable operating where the question is unclear, the data is imperfect, and the answer matters. Desired Advanced Analytics in a Workforce Context: Hands-on experience applying predictive or machine learning techniques to people data - attrition modelling, skills clustering, internal mobility analysis, or similar. Cross-Domain People Analytics: Experience spanning more than one analytics domain - e.g. engagement, succession planning, workforce planning, and DEI - with the ability to connect insights across them. Global & Multi-Jurisdictional Data: Experience managing and interpreting datasets across multiple geographies, including navigating data privacy constraints. Consulting or Embedded Advisory Experience: #J-18808-Ljbffr