Advisory analytics manager
Pubblicato il 13-08-2026 - Anonymous in Italia
Advisory Analytics Manager – EMEA – Milano, Italy At Aon we build decisions for the better safeguarding and enriching the lives of people worldwide. Our colleagues provide clients in over 120 countries with advice and solutions that give them the clarity and confidence to make better decisions to protect and grow their business. Our Analytics Team helps organisations make better workforce decisions by applying quantitative methods, statistical analysis, and sophisticated people analytics across human capital, compensation, and talent topics. We support clients on compensation fairness, clarity in remuneration and reward equity, and help HR professionals and business leaders understand workforce dynamics and link talent outcomes to business performance. We combine Aon's proprietary datasets with client data to answer strategic questions using meticulous analytical techniques, including pay equity modelling, segmentation, benchmarking, predictive modelling, driver analysis, and workforce diagnostics related to reward, talent acquisition, deployment, retention, workforce planning,
and business performance. Core Responsibilities Interrogate large, sophisticated, and often imperfect client and proprietary datasets to identify workforce, reward, and talent patterns, including potential pay equity issues, data anomalies, and opportunities for evidence‐based insight. Lead or run elaborate analytics engagements from problem definition and data specification through data preparation, methodology selection, model development, validation, and interpretation of results across topics such as pay equity, pay transparency, workforce planning, reward analytics, and predictive people analytics. Synthesise sophisticated quantitative outputs into clear narratives, translating statistical findings, pay equity diagnostics, model results, and benchmark comparisons into practical implications and recommendations for HR and organisational decision‐makers. Build analytically robust solutions