Global Data Senior Analyst
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Global Data Senior Analyst (Commercial Analytics): Powering strategic decisions and operational excellence through weekly performance reporting, deep-dive analyses, and insight generation for pricing, assortment, promotions, and inventory optimization across 's global travel retail network. Focus on uncovering hidden insights, validating data science models, and delivering actionable recommendations to C-suite executives under tight deadlines.
Location: Madrid Office, Milan Office
Company
World's leading travel experience player operating 5,500 outlets in over 75 countries, focusing on travel retail and F&B at airports, motorways, and other locations.
What you will do
- Own weekly commercial performance reporting: analyze sales trends, margins, pricing, promotions, and competition across categories, regions, and locations.
- Prepare executive dashboards and deep-dives on performance variances, attributing changes to key drivers.
- Monitor KPIs for pricing, assortment, promotions, and inventory; respond rapidly to urgent C-level questions.
- Partner with data scientists: provide datasets, conduct EDA, validate models, and support A/B tests.
- Proactively generate insights, build self-serve dashboards, and present findings to commercial teams.
- Collaborate with IT/BI to resolve data issues and maintain documentation.
Requirements
- Expert SQL for complex queries on large datasets.
- Advanced Excel; Python or R for data manipulation.
- Strong statistics: descriptive stats, regression, hypothesis testing.
- 5–8 years in commercial analytics, BI, or FP&A in retail, e-commerce, travel, or FMCG.
- Deep commercial knowledge: pricing, margins, promotions, P&L.
- Executive communication skills; fluency in English (written & spoken).
Nice to have
- Bachelor's in quantitative field or equivalent.
- BI tools experience (Tableau, Power BI).
- Exposure to data science/ML projects.
- Background in pricing/revenue management or merchandising analytics.
- Python proficiency; management consultancy or tech experience.
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