Fraud Data Analyst — Trusted Analytics Advisor

LexisNexis Risk Solutions; Georgia; On-site; USD 105,000 - 175,000; Full time

Job summary

LexisNexis Risk Solutions seeks a Fraud Data Analyst to support large banking, financial services, and e-commerce clients in implementing, optimizing, and managing fraud and identity solutions. You will blend data analytics, fraud investigation, and technical consulting while engaging with clients to drive measurable outcomes.

The ideal candidate is highly analytical, client-focused, and capable of translating complex findings into actionable recommendations.

Qualifications

• Bachelor's degree in a quantitative, technical, analytical, or related field.
• 3+ years of experience supporting customer-facing technology, analytics, or fraud prevention solutions.
• 3+ years of experience in financial services, banking, fintech, payments, risk management, or e-commerce environments.
• 3+ years of experience performing advanced analytics using Python (including pandas, scikit-learn, and matplotlib), R, or similar analytical tools.
• Strong proficiency with SQL and Excel for data analysis, reporting, and performance monitoring.
• Experience investigating fraud, financial crimes, or suspicious activity, including account takeover, card-not-present fraud, money laundering, and social engineering attacks.
• Demonstrated ability to perform root cause analysis and solve complex business and technical challenges.
• Strong communication and presentation skills with the ability to translate technical findings into business-focused recommendations.
• Proven ability to manage multiple priorities in a fast-paced, client-facing environment.
• Strong customer service mindset with a passion for helping clients achieve measurable business outcomes.

Responsibilities

• Review suspicious activity, fraud alerts, and complex fraud cases to identify emerging risks, trends, and vulnerabilities.
• Analyze large datasets to build, optimize, and maintain fraud detection rules, models, and workflows that improve fraud prevention and operational efficiency.
• Conduct root cause analyses to investigate client issues, identify contributing factors, and develop effective solutions.
• Deliver impactful analyses and recommendations to both technical and non-technical stakeholders through presentations, reports, and client consultations.
• Advise clients on best practices for implementing and optimizing ThreatMetrix® Digital Identity Network, Digital Device Profiling (DDP), and other LexisNexis Risk Solutions products.
• Partner with clients to improve fraud mitigation strategies while balancing customer experience and operational objectives.
• Perform proof-of-concept analyses and demonstrate measurable business value through data-driven insights.
• Collaborate closely with fraud managers, risk analysts, developers, project managers, and other customer stakeholders to support solution adoption and performance optimization.
• Build and maintain strong client relationships by serving as a trusted consultant and subject matter expert.
• Develop reports, dashboards, and analytical deliverables using SQL, Excel, Python, R, and other analytics tools.
• Research emerging fraud techniques, cybersecurity trends, and financial crime risks to provide proactive recommendations.
• Support internal teams with product feedback, solution enhancements, and client-related insights.

Skills

Analytical thinking

Customer-facing

Communication

Fraud detection

Multitasking

Problem solving

Education

Bachelor's degree in a quantitative, technical, analytical, or related field

Tools

Python

R

SQL

Excel

Job description

LexisNexis Risk Solutions seeks a Fraud Data Analyst to support large banking, financial services, and e-commerce clients in implementing, optimizing, and managing fraud and identity solutions. You will blend data analytics, fraud investigation, and technical consulting while engaging with clients to drive measurable outcomes.

The ideal candidate is highly analytical, client-focused, and capable of translating complex findings into actionable recommendations.