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Asset Data Analyst

2 months ago

London, Greater London, United Kingdom Burberry Full time
Job Purpose

As a Loss Prevention Data Analyst at Burberry, you will play a critical role in providing data-driven insights to identify and mitigate potential risks within the organization. Your expertise will be instrumental in ensuring the integrity of our operations and protecting our assets.

This is a full-time, permanent position based in our London office, requiring a minimum of two days of on-site work per week.

Key Responsibilities
  • Maintain the Asset and Profit Protection (APP) Operations database, ensuring accurate and up-to-date store master and HR data.
  • Provide ad-hoc support to the Digital Fraud team, focusing on chargebacks and payment issues.
  • Cleanse and analyze monthly incident and investigation data to inform business decisions.
  • Manage and maintain departmental Power apps, ensuring seamless data integration and reporting.
  • Develop and maintain departmental Power BI reporting, providing weekly and monthly insights to stakeholders.
  • Oversee the maintenance of the APP Hub on SharePoint, ensuring secure and efficient data storage.
  • Support the whistleblowing line and gifts & hospitality register, providing data cleansing and administrative assistance.
  • Contribute to biannual stock loss reporting, performing data analysis and providing recommendations for improvement.
Personal Profile
  • Advanced proficiency in the Office 365 Suite, particularly Excel.
  • Experience with Power Platforms, including data modeling and visualization.
  • Strong analytical and problem-solving skills, with a data-driven approach.
  • Background in retail fraud prevention, with a focus on data analysis and risk mitigation.
  • Experience with Microsoft Access and SAP, with a strong understanding of data management systems.
  • Fluency in English, both written and verbal, is essential for effective communication.

Burberry is an Equal Opportunities Employer, committed to recruiting based on skills and experience, without bias or prejudice.