Fraud Data Analyst

atRELXRemoteUS flagNew YorkFull-timeData AnalystMid-levelSenior$115.4k – $192.2k/year

Posted Sep 24

This is a fully remote position, open to applicants in New York.

📋 Description

• Examine suspicious activities, fraud alerts, and intricate fraud cases to pinpoint emerging risks, trends, and weaknesses.

• Evaluate extensive datasets to create, enhance, and sustain fraud detection rules, models, and workflows.

• Perform root cause analyses to address client challenges and formulate solutions.

• Present analyses and recommendations through reports, presentations, and client consultations.

• Counsel clients on the implementation and optimization of ThreatMetrix Digital Identity Network, Digital Device Profiling, and other LexisNexis Risk Solutions offerings.

• Collaborate with clients to enhance fraud mitigation strategies while maintaining a balance between customer experience and operational goals.

• Conduct proof-of-concept analyses and showcase business value via data-driven insights.

• Work alongside fraud managers, risk analysts, developers, project managers, and customer stakeholders.

• Establish and nurture client relationships as a trusted advisor and subject matter expert.

• Create reports, dashboards, and analytical outputs utilizing SQL, Excel, Python, R, and other analytics tools.

• Investigate emerging fraud techniques, cybersecurity developments, and financial crime risks.

• Assist internal teams with product feedback, solution enhancements, and insights related to clients.


⛳️ Requirements

• A bachelor's degree in a quantitative, technical, analytical, or related discipline.

• Over 3 years of experience in customer-facing technology, analytics, or fraud prevention solutions.

• More than 3 years of experience in financial services, banking, fintech, payments, risk management, or e-commerce sectors.

• 3+ years of advanced analytics experience using Python, R, or equivalent analytical tools.

• Proficiency in Python, including libraries such as pandas, scikit-learn, and matplotlib.

• Strong expertise in SQL and Excel.

• Experience in investigating fraud, financial crimes, or suspicious activities, including account takeover, card-not-present fraud, money laundering, and social engineering attacks.

• Ability to conduct root cause analyses and solve complex business and technical problems.

• Excellent communication and presentation capabilities.

• Capacity to handle multiple priorities in a dynamic, client-facing setting.

• Strong customer service orientation.

• Preferred: experience in fraud prevention, digital identity, authentication, risk management, or financial crime solutions.

• Preferred: knowledge of cybersecurity concepts, including browser fingerprinting, device intelligence, PKI, computer networking, and device authentication.

• Preferred: familiarity with ThreatMetrix or comparable fraud and identity platforms.

• Preferred: experience with machine learning, predictive analytics, statistical modeling, scorecard development, or graph analytics.

• Preferred: experience in developing fraud detection strategies and risk-based decision-making frameworks.

• Preferred: understanding of AML, KYC, fraud operations, and regulatory compliance practices.

• Preferred: experience with enterprise banking, financial services, or large e-commerce organizations.


🏝️ Benefits

• Annual incentive bonus.

• Country-specific benefits.

• Disability and accommodation support throughout the hiring process.

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