Advisory analytics manager - emea

  • Pubblicato il 04/07/2026
  • Roma (RM)
  • Da definire

Descrizione:

Experteer Overview In this role you drive data-driven workforce insights for HR and leadership across Europe, Middle East, and Africa. You will oversee analytics projects that combine client data with Aon datasets to answer strategic questions on pay equity, talent, and rewards. Expect to translate complex analyses into practical recommendations that influence compensation and workforce planning. The role blends technical rigor with client-facing leadership, delivering impact at scale in a fast-growing advisory practice. Retribuzione / Benefits Interrogate large, complex datasets to identify workforce, reward, and talent patterns; surface pay equity issues and data anomalies Lead or manage end-to-end analytics engagements from problem definition to result interpretation across pay equity, transparency, workforce planning, and predictive analytics Synthesize quantitative outputs into clear narratives and practical recommendations for HR and executives Build robust data-driven solutions by defining data strategy, modelling approach, and outputs while balancing technical depth with commercial feasibility Demonstrate commercial leadership by translating client requirements into compelling proposals and insights Responsabilità Bachelor's degree in Statistics, Data Science, Economics, or Mathematics; postgraduate analytics training is advantageous Experience with statistical methods and techniques (e.g., regression, hypothesis testing, segmentation, trend analysis) Hands‑on work with large HR/reward/workforce datasets using Python, R, SQL or equivalent Significant experience in consulting or corporate analytics, especially in pay equity, compensation, or people analytics Strong data visualization and insight communication skills using Tableau or Power BI Meticulous, curious mindset with attention to data limitations and problem‑solving discipline Excellent verbal and written communication, able to explain methods and findings to non-technical audiences #J-18808-Ljbffr