Fraud Data Analyst

About the role

The Fraud Data Analyst will act as a trusted advisor and analytical consultant, helping banking, financial services and e‑commerce clients implement, optimize and manage fraud and identity solutions. The role blends data analytics, fraud investigation, technical consulting and client engagement to improve fraud prevention while minimizing friction for legitimate customers.

Key responsibilities

• Review suspicious activity, fraud alerts and complex cases to identify emerging risks and trends.
• Analyze large datasets to build, optimize and maintain fraud detection rules, models and workflows.
• Conduct root‑cause analyses, develop solutions and deliver recommendations to technical and non‑technical stakeholders.
• Advise clients on best practices for ThreatMetrix® Digital Identity Network and Digital Device Profiling.
• Partner with clients to improve fraud mitigation strategies while balancing customer experience.

Required profile

• Bachelor’s degree in a quantitative, technical or analytical field.
• 3+ years experience supporting customer‑facing technology, analytics or fraud prevention solutions.
• 3+ years experience in financial services, banking, fintech, payments or e‑commerce.
• Proven ability to perform root‑cause analysis and solve complex business and technical challenges.

Required skills

• Python (pandas, scikit‑learn, matplotlib) and R for advanced analytics.
• Strong proficiency with SQL and Excel for data analysis and reporting.
• Experience with ThreatMetrix® or similar digital identity and fraud platforms.
• Knowledge of machine learning, predictive analytics, statistical modeling and scorecard development.