Omnichannel Performance Analyst
Pubblicato il 10-09-2026 - Pvh Italy in Milano
Stone Island is a defiantly independent community. Since our founding in 1982, a shared mindset has driven us to become a globally recognized icon of independent spirit, leadership, and innovation. The Stone Island spirit is the foundation of the culture that we cherish and nurture every day. We provide you with the opportunity to build relationships that will shape your career, your life and our famiglia. The opportunity to follow your own compass.
The Role
Omnichannel Performance Analyst
We are currently looking for an engaged and passionate Omnichannel Performance Analyst who can join our Team at Stone Island HQ in Milan.
Your Impact
Main Activities
- Monitor the performance of DOS, Digital, Wholesale and Outlet channels, identifying key trends, performance drivers, and unexpected variances to support business discussions and decision‑making.
- Turn large‑scale data into clear and actionable business insights, connecting performance results with their underlying drivers and translating them into concrete business actions.
- Develop ad‑hoc analyses on Sales & KPIs,
Sell‑through, Product Mix, Client behaviour and Market dynamics.
- Support the team in preparing periodic omnichannel performance reports at Global and Regional level, ensuring accuracy and consistency.
- Build and maintain advanced Excel files, dashboards, and analytical tools to improve the tracking and interpretation of business performance.
- Contribute to business reviews, presentations, and strategic projects at WW level, supporting the preparation of materials for HQ, Regions and Top Management.
- Liaise with the IT and BI teams to ensure accurate, updated, and efficient reporting tools, while contributing to the continuous improvement and automation of reporting processes.
- Become a point of reference for all the internal stakeholders, including Regions, Finance, Retail, Digital, Wholesale, Merchandising and Distribution.
Qualifications
- Degree in Economics, Statistics, Engineering, Data