Fraud Data Analyst

Fraud Data Analyst

Requirements

• Native or fluent in English
• Ability to travel domestically up to 10%
• Quantitative or technical degree
• 2+ years of experience managing large customer-facing solutions
• 2+ years of experience in insurance, government, healthcare, or financial services organizations
• 2+ 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
• 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

Responsibilities

• 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 ThreatMetrix DDP, Behavioral and other LexisNexis Risk Solutions.
• Maintain ongoing relationships with each client’s fraud managers, risk analysts, application developers, project managers as well as internally with other LexisNexis Risk Solutions teams

Preferred Qualifications

No preferred qualifications provided.