Fraud Data Analyst
RELX (Elsevier, LexisNexis) · Remote · New York +1 · 1d ago
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
LexisNexis® Risk Solutions helps organizations make better decisions by leveraging data, advanced analytics, and technology to evaluate and predict risk, detect fraud, and combat financial crime. Our solutions empower customers across banking, financial services, and e-commerce to address challenges such as identity theft, account takeover, money laundering, social engineering, and other emerging fraud threats.
Our Fraud and Identity Professional Services team works directly with leading financial institutions and global organizations to optimize fraud prevention strategies and maximize the value of LexisNexis Risk Solutions products. We are a collaborative team of consultants, analysts, and subject matter experts who combine technical expertise, data-driven insights, and industry knowledge to help clients reduce risk, improve customer experiences, and stay ahead of evolving fraud trends.
About the Role
The Fraud Data Analyst serves as a trusted advisor and analytical consultant, supporting large banking, financial services, and e-commerce clients in the implementation, optimization, and ongoing management of fraud and identity solutions. This role blends data analytics, fraud investigation, technical consulting, and client engagement.
The ideal candidate is highly analytical, customer-focused, and passionate about solving complex fraud and risk challenges. You will work closely with clients to assess fraud patterns, analyze performance data, develop detection strategies, and provide actionable recommendations that improve fraud prevention outcomes while minimizing friction for legitimate customers.
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.
Requirements
Required 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 working within 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.
Preferred Qualifications
- Experience with fraud prevention, digital identity, authentication, risk management, or financial crime solutions.
- Knowledge of cybersecurity concepts, including browser fingerprinting, device intelligence, public key infrastructure (PKI), computer networking, and device authentication.
- Experience with ThreatMetrix® solutions or similar fraud and identity platforms.
- Familiarity with machine learning, predictive analytics, statistical modeling, scorecard development, or graph analytics.
- Experience developing fraud detection strategies and risk-based decisioning frameworks.
- Knowledge of AML, KYC, fraud operations, and regulatory compliance practices.
- Experience working directly with enterprise banking, financial services, or large e-commerce organizations.
- Ability to influence client strategy and serve as a trusted advisor across both business and technical teams.


U.S. National Base Pay Range: $104,900 - $174,700. Geographic differentials may apply in some locations to better reflect local market rates.

If performed in New York, the base pay range is $115,400 - $192,200.If performed in New York City, the base pay range is $125,900 - $209,700.If performed in Rochester, NY, the base pay range is $104,900 - $174,700.

This job is eligible for an annual incentive bonus.






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