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Fraud data analyst

London
LexisNexis Risk Solutions
Data analyst
Posted: 19 August
Offer description

Conducting in-depth reviews of complex fraud cases: Identifying trends and actionable insights, documenting findings, and making clear recommendations on how to mitigate risk.

Using SQL and Python skills: Increasing fraud capture, reducing false positives, analyzing customer data offline to expose patterns, tuning policies statistically, producing executive reports, and owning the end-to-end delivery of recommendations by writing rules into the ThreatMetrix decision engine.

Building dashboards & reports: Tracking the value delivered, focusing on external-facing dashboards that surface key insights to each customer.

Data storytelling and presentation: Crafting stories through data, delivering industry-leading presentations to external and executive audiences with non-technical backgrounds.

Project management: Scoping, planning, and delivering customer-focused projects including root cause analysis, reports, dashboards, rule mining, and health checks. Demonstrating professionalism and customer-centricity in interactions via phone, email, and chat.

Collaboration: Working with ThreatMetrix teams including Products, Engineering, Sales, and Professional Services worldwide to redefine best practices.

Experience required: Within a Fraud Strategy or Fraud Analytics function, proficient in SQL, Python, and BI tools like SuperSet, PowerBI, Tableau (bonus), with experience in fraud system management (ThreatMetrix, Emailage, Featurespace, Hunter, Iovation, BioCatch, Actimize Falcon, etc.), and interest or experience in consulting within risk, fraud, or payments industries.

Skills and qualities: Attention to detail, ability to build external and executive reports, multi-tasking, prioritization, and ability to excel in a fast-paced environment with changing priorities.

About the Business: LexisNexis Risk Solutions helps businesses assess risk, drive revenue, optimize operations, and improve customer experience across areas like AML, identity verification, fraud mitigation, and customer data management.

About our Team: A team of analysts using global data from a large real-time fraud detection platform to optimize solutions for enterprise customers.

About the Role: Using data analysis to investigate suspicious behavior, providing insights that reduce fraud losses, lower customer friction, and increase profitability. Analyzing billions of transactions per month for clients in financial services, insurance, e-commerce, and on-demand services, collaborating across teams to build effective policies against motivated attackers.

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