Senior Fraud Data Analyst

About The Business

Lexis Nexis® Risk Solutions provides customers with solutions and decision tools that assist them in evaluating and predicting risk and enhancing fraud detection. We use the power of data and advanced analytics to help our customers make better, timelier decisions. Our innovative solutions enable our clients to manage risks like identity theft, fraud, money laundering and terrorism, and prevent financial crimes.

Our core mission is to ultimately help make communities safer and to protect those who may be vulnerable to fraud. Drawing from the collective expertise of our experienced team, we continuously evolve to stay a step ahead of fraudsters. Every day, as millions go about their lives, it is our behind‑the‑scenes efforts that ensure their security, giving them the confidence to trust and engage online without fear of being de‑frauded.

This client facing team is driving evidence‑based solutions to help our clients make more informed decisions and help mitigate risk.

The Senior Fraud Data Analyst works as part of a customer engagement team to support Tier One large banking, financial, and e‑commerce customers in their deployment of fraud and identity solutions. This is primarily a consultant role with a technical and analytics bent.

• Review suspicious activity and complex fraud cases to identify new risks and issues.
• Analyze data in order to build and adjust rules that identify fraud, reduce friction, and regulate customer workflows in real‑time.
• Deliver persuasive analyses to both technical and non‑technical audiences – sometimes in‑person at the customer site.
• Advise clients on best practices for their technical implementation and analysis of Threat Metrix DDP and other Lexis Nexis Risk Solutions, and maintain ongoing relationships with each client’s fraud managers, risk analysts, application developers, project managers as well as internally with other Threat Metrix LNRS teams.

• Quantitative or technical degree.
• 3+ years of experience managing large customer‑facing solutions.
• 3+ years of experience in financial services, banks, or e‑commerce organizations.
• 3+ years of experience delivering analytics using tools such as Python (pandas, sklearn, matplotlib) or R.
• Demonstrated competence using SQL and Excel for reports.
• Willingness to conduct root‑cause analysis of client’s issues and learn new products.
• Motivated to help customers succeed and deliver value through proof‑of‑concept analysis.
• Excellent communication skills, with the ability to present technical findings to non‑technical stakeholders.
• Extensive multi‑tasking and prioritization skills. Needs to excel in fast‑paced environment with frequently changing priorities.
• Experience investigating financial crimes and fraud – account takeover, card not present, money laundering, social engineering, etc.
• Knowledge or research involving cybersecurity – browser‑fingerprinting, public key infrastructure, computer networking, device authentication, etc.
• Experience in statistical/scorecard modeling or graph analysis to deliver insights – especially as it pertains to credit risk or fraud detection.

U.S. National Base Pay Range: $104,900 - $174,700. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus.