Senior Fraud Data Analyst

About the Role

Key Responsibilities

• Work with VP of Fraud Management and Director of Fraud Prevention and Analytics to define and execute the strategic plan for fraud prevention platforms, including rules, models, and detection systems.
• Analyze data and leverage fraud tools to identify emerging fraud risks such as identity theft, money mule scams, and account fraud across various transaction types including debit/credit cards, checks, wires, ACH, Billpay, and Zelle.
• Develop and utilize advanced analytics techniques (machine learning, AI) to identify, mitigate, and respond in real-time to fraud patterns, threats, and trends.
• Perform root cause analysis following fraud events and provide actionable recommendations for remediation.
• Keep current on developments in data management, analysis, visualization, behavioral profiling, machine learning, and AI related to fraud prevention.
• Collaborate with Model Risk Management Committee to ensure fraud detection models are compliant and effective, contributing to model validation and risk assessments.
• Document and maintain fraud prevention strategies, rules, model documentation, and fraud data.
• Create dashboards and KPIs to track fraud performance and measure prevention strategies.
• Communicate results proactively to Fraud leadership and executive management.
• Assess, prioritize, and deliver projects impacting core business workstreams.
• Perform routine audits of monitoring data quality and coverage.
• Analyze fraud trends and contribute to fraud intelligence reports.
• Support development of fraud KPIs and dashboards to measure risk and mitigation effectiveness.
• Document fraud incidents, case resolutions, and lessons learned for continuous improvement.
• Partner with technology and data teams to support fraud data analytics needs and ensure data policy compliance.

Requirements

• Eight years' experience in fraud prevention within a progressive analytics position, specifically in a financial fraud setting.
• Bachelor's degree in data analytics, statistics, business, or related field from an accredited institution; Master’s or doctorate preferred.
• Advanced skills with Microsoft Office Suite (Outlook, Word, PowerPoint, Excel).
• Experience with data visualization tools such as Power BI and Tableau.
• Proficiency in research, advanced statistical methods, and analytic tools including R, Python, SAS, SPSS, SQL.
• Experience with fraud risk scoring, machine learning-based fraud detection, or SIEM tools like Splunk or ArcSight.
• Knowledge of complex data systems, including many-to-many databases and cross-server data solutions.
• Ability to analyze data for patterns and trends and communicate findings effectively.
• Experience working in Fraud Analytics or Investigations within the Financial Services industry.
• Strong communication skills and ability to collaborate with internal stakeholders.

Nice to Have

• Certifications such as CFE (Certified Fraud Examiner), CISA, CISSP, or CEH.

Qualifications

• Bachelor's degree in data analytics, statistics, business, or related field.
• Master or doctorate degree preferred.

Benefits & Perks

• Not explicitly specified in the description.