Fraud Data Analyst
Human API
Accounting & Finance, IT, Data Science
Georgia, USA
About the Business
LexisNexis® 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's our behind-the-scenes efforts that ensure their security, giving them the confidence to trust and engage online without fear of being de-frauded.
About the Team:
This client facing team is driving evidence-based solutions to help our clients make more informed decisions and help mitigate risk.
About the Role:
The Fraud Data Analyst works as part of a customer engagement team to support 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.
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 and other LexisNexis Risk Solutions Maintain on-going relationships with each client’s fraud managers, risk analysts, application developers, project managers as well as internally with other ThreatMetrix LNRS teams
Qualifications:
Quantitative or technical degree
2+ years of experience managing large customer-facing solutions
2+ years of experience in financial services, banks, or e-commerce 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
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
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