Fraud Data Analyst – Advanced Analytics & Client Advisory

About the role

The Fraud Data Analyst serves as a trusted advisor and analytical consultant, supporting large banking, financial services, and e‑commerce clients in implementing and optimizing fraud and identity solutions. This role blends data analytics, fraud investigation, technical consulting, and client engagement. The ideal candidate is highly analytical, customer‑focused, and passionate about solving complex fraud and risk challenges.

Key responsibilities

• Review suspicious activity, fraud alerts, and complex cases to identify emerging risks, trends, and vulnerabilities.
• Analyze large datasets to build, optimize, and maintain fraud detection rules, models, and workflows.
• Conduct root‑cause analyses, develop solutions, and deliver actionable recommendations to technical and non‑technical stakeholders.
• Advise clients on best practices for ThreatMetrix® Digital Identity Network, Digital Device Profiling, and other LexisNexis Risk Solutions products.
• Develop reports, dashboards, and analytical deliverables using SQL, Excel, Python, and R.

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, risk management, or e‑commerce.
• 3+ years performing advanced analytics with Python (pandas, scikit‑learn, matplotlib) or R.
• Strong proficiency with SQL and Excel for data analysis and reporting.
• Experience investigating fraud, financial crimes, or suspicious activity.
• Proven ability to perform root‑cause analysis and solve complex business and technical challenges.
• Excellent communication and presentation skills, with a customer‑service mindset.

Required skills

• Python (including pandas, scikit‑learn, matplotlib)
• R
• SQL
• Excel
• ThreatMetrix® Digital Identity Network (or similar fraud/identity platforms)