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KERING Category Platform Data Analyst

Pubblicato il 21-09-2026 - Kering in Pavia

Overview As a Category Platform Data Analyst, you enable data-driven decisions for Leather Goods, RTW, Shoes, Tannery, and Metal Hardware platforms. You will provide reliable data, analyses, and executive-ready insights to platform leadership and PMO, focusing on volume allocation, capacity, and supplier performance. Your work supports governance, standardization, and continuous improvement of platform data and reporting. This role combines analytics with cross-brand collaboration to drive operational efficiency and transparency.
Retribuzione / Benefits
- Starting gross salary: 30 000 per year
- Annual premio opportunity
- Company canteen
- Welfare initiatives
- Benefits in line with national collective agreement
- Diversity and inclusion commitment

Responsabilità
- Collect and consolidate data inputs (volume requirements, allocations, capacity)
- Ensure data accuracy and transparency across Brands and Categories
- Analyze volume allocation and capacity utilization, highlighting risks and deviations
- Report capacity deviations to the Mutualized Production Assets Lead




- Provide analytical views and scenario simulations for platform discussions
- Analyze supplier performance data across key KPIs
- Develop and maintain platform dashboards and KPI reporting (Power BI, Excel)
- Prepare executive-ready analyses and presentations for Platform governance
- Support PMO and procurement leads with structured data and insights
- Contribute to standardization of indicators, reporting logic, and data models
- Support continuous improvement initiatives to enhance data quality and analytics

Requisiti fondamentali
- Strong analytical mindset with ability to structure complex data
- Proficient in Excel, PowerPoint, and Power BI; building dashboards and reports
- Experience with recurring data cycles (monthly allocation, capacity monitoring, supplier tracking)
- Master’s degree in a quantitative field
- Previous experience in data analysis, operations analytics, supply chain, or con

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