Fraud Data Analyst

RELX; Georgia; On-site; USD 105,000 - 175,000; Full time

Benefits offered by this job

Annual incentive bonus

Job summary

RELX invites seasoned professionals to join a customer engagement team delivering fraud and identity analytics for banking, financial, and e-commerce clients. You will review complex cases, develop analytics-driven rules, and present findings to both technical and non-technical audiences, including on-site demonstrations.

Ideal candidates bring 3+ years in financial services or e-commerce, strong Python/R/SQL skills, and the ability to translate data into risk insights that improve client

Qualifications

• 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 Python (pandas, sklearn, matplotlib) or R.
• Demonstrated competence with SQL and Excel for reporting.
• Ability to conduct root-cause analysis of client issues and learn new products.
• Motivation to help customers succeed through value delivered via proof-of-concept analysis.
• Strong communication skills, including presenting technical findings to non-technical stakeholders.
• Extensive multi-tasking and prioritization skills to excel in a fast-paced environment with frequently changing priorities.
• Experience investigating financial crimes and fraud, including account takeover, card not present, money laundering, and social engineering.
• Knowledge or research in cybersecurity areas such as browser fingerprinting, public key infrastructure, computer networking, and device authentication.
• Experience with statistical/scorecard modeling or graph analysis to generate insights related to credit risk or fraud detection.

Responsibilities

• Review suspicious activity and complex fraud cases to surface new risks and issues.
• Analyze data to create and refine fraud detection rules that identify fraudulent behavior.
• Optimize rules to reduce friction and regulate customer workflows in real time.
• Provide clear, persuasive analyses to technical and non-technical audiences, including occasional on-site customer presentations.
• Advise clients on best practices for technical implementation and analysis of ThreatMetrix DDP and other LexisNexis Risk Solutions.
• Maintain ongoing relationships with client stakeholders including fraud managers, risk analysts, application developers, and project managers.
• Collaborate internally with other ThreatMetrix / LNRS teams to support client outcomes.

Skills

Fraud analytics experience

Client-facing experience

Financial services industry knowledge

Analytical mindset

Strong communication

Education

Quantitative or technical degree

Tools

Python (pandas, sklearn, matplotlib)

R

SQL

Excel

ThreatMetrix DDP

Job description

Join a customer engagement team supporting banking, financial, and e-commerce clients with fraud and identity analytics solutions.

Responsibilities

• Review suspicious activity and complex fraud cases to surface new risks and issues
• Analyze data to create and refine fraud detection rules that identify fraudulent behavior
• Optimize rules to reduce friction and regulate customer workflows in real time
• Provide clear, persuasive analyses to technical and non-technical audiences, including occasional on-site customer presentations
• Advise clients on best practices for technical implementation and analysis of ThreatMetrix DDP and other LexisNexis Risk Solutions
• Maintain ongoing relationships with client stakeholders including fraud managers, risk analysts, application developers, and project managers
• Collaborate internally with other ThreatMetrix / LNRS teams to support client outcomes

Requirements

• 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 Python (pandas, sklearn, matplotlib) or R
• Demonstrated competence with SQL and Excel for reporting
• Ability to conduct root-cause analysis of client issues and learn new products
• Motivation to help customers succeed through value delivered via proof-of-concept analysis
• Strong communication skills, including presenting technical findings to non-technical stakeholders
• Extensive multi-tasking and prioritization skills to excel in a fast-paced environment with frequently changing priorities
• Experience investigating financial crimes and fraud, including account takeover, card not present, money laundering, and social engineering
• Knowledge or research in cybersecurity areas such as browser fingerprinting, public key infrastructure, computer networking, and device authentication
• Experience with statistical/scorecard modeling or graph analysis to generate insights related to credit risk or fraud detection

Tools and Technologies

• Python (pandas, sklearn, matplotlib)
• R
• SQL
• Excel
• ThreatMetrix DDP

Location and Compensation

• Location: Georgia (onsite)
• Base pay range: USD 104,900 - 174,700 per year
• Incentive: Eligible for an annual incentive bonus