Fraud Data Analyst – Hybrid (Oxford)

About the role

We are seeking a hands‑on Fraud Data Analyst to join our fast‑moving Trust & Safety team in Oxford. Working one day a week on‑site and the rest remotely, you will analyse large‑scale transaction data to uncover fraud patterns and support investigations.

Key responsibilities

• Analyse large‑scale transaction and payment data to identify fraud trends and root causes.
• Combine multiple data sources to uncover actionable insights.
• Develop recommendations, fraud controls, alerts, and operational improvements.
• Support fraud and chargeback investigations.
• Produce operational and performance reporting.
• Identify opportunities for automation and process improvement.
• Present complex findings clearly to technical and non‑technical stakeholders.

Required profile

• Strong hands‑on SQL skills and experience with large datasets.
• Proven ability to investigate issues, identify root causes and drive business action.
• Excellent data storytelling and stakeholder communication.
• Curious, proactive mindset with interest in automation and AI‑assisted analysis.

Required skills

• SQL
• BigQuery
• Tableau
• Looker
• Python
• SPSS
• Jira
• AI tools such as Claude, Gemini, or Cursor
• Workflow automation tools such as n8n