Zuru
Sales Analyst
Bentonville | United States
Sponsorship not specifiedDetected 69 days ago
Data VisualizationSalesAccount ManagementExcelSupply ChainCollaborationPublic SpeakingMicrosoft OfficeDemand Planning
About the role
- Apply now to join ZURU Edge as a Business Analyst!
- ZURU Beauty is in a phase of explosive growth, driven by disruptive new brands and innovations.
- You'll work with iconic brands like MONDAY Haircare and DAISE, while helping launch exciting new brands.
Requirements
- Proficiency in Microsoft Excel (advanced: PivotTables, XLOOKUP, modelling) and PowerPoint the ability to build clean, insight-led slides under pressure is a must.
- Experience with at least one major retail data platform: Quantium, NIQ/NielsenIQ Scan, Circana/IRI, Coles 360, or similar.
- Moves fast without sacrificing accuracy you know when good enough is good enough, and when precision matters.
- Essential
- Excellent attention to detail with the ability to manage multiple data streams and deadlines simultaneously.
- Highly Regarded
- 1-3 years of experience in a Sales Analyst, Category Analyst, Commercial Analyst, or Account Executive support role ideally within FMCG, beauty, personal care, or consumer healthcare.
- The Person We Are Looking For
- Beyond the technical skills, we're looking for someone who:
Nice to have
- Quantium, NIQ/NielsenIQ Scan, Circana/IRI, Coles 360, or similar.
- Strong commercial instincts you can look at a number and know whether it's telling a good story or hiding a problem.
- Confident communicator who can distil complex data into clear, concise insights for non-analytical audiences.
- Experience working directly with major grocery or pharmacy retailers
- A Bachelor's degree in Business, Commerce, Marketing, Economics, or a related discipline.
- Experience with data visualisation tools such as Power BI or Tableau.
Skills
- Thrives in a high-growth, entrepreneurial environment where priorities can shift and no two weeks look the same.
This listing is sourced directly from Zuru's careers page and normalized into a canonical job model.