KERING Category Platform Data Analyst
Pubblicato il 12-08-2026 - Kering in Firenze
SummaryKering is a global, family-led luxury group, home to people whose passion and expertise nurture creative Houses across couture and ready-to-wear, leather goods, jewelry, eyewear and beauty: Gucci, Saint Laurent, Bottega Veneta, Balenciaga, McQueen, Brioni, Boucheron, Pomellato, Dodo, Qeelin, Ginori 1735, as well as Kering Eyewear. Inspired by their creative heritage, Kering Houses design and craft exceptional products and experiences that reflect the Group’s commitment to excellence, sustainability and culture. This vision is expressed in our signature: Creativity is our Legacy. In 2025, Kering employed 44,000 people and generated revenue of 14.7 billion.Job DescriptionThe Group Industrial Organization is responsible for enabling transparency across Brands, supporting industrial and supplier mutualization, and enabling data-driven decision-making across Categories. Kering Industrial Organization is currently seeking a Category Platform Data Analyst, who will report to the Head of Strategic opportunityAs a Category Platform Data Analyst,
you will play a key role in supporting Category Platforms (Leather Goods, RTW, Shoes, Tannery, Metal Hardware) by providing reliable data, robust analyses, and clear performance insights.You will work closely with Platform leadership, the Platform PMO, the Direct Procurement lead/ the Mutualized Production Assets lead, acting as a data and analytics backbone for platform‑level discussions on volume allocation, capacity, and supplier performance.The role is analytical and support‑focused, with no direct ownership of procurement strategy or PMO execution.How you will contributeCollect, consolidate, and maintain Brands’ data inputs, including volume requirements, allocation proposals, reallocations, and capacity informationEnsure accuracy, consistency, and transparency of platform data across Brands and Categories, acting as a reference point for data reliabilityAnalyze volume allocation and capacity utilization across internal a