Fraud Data Analyst

About the position The role of Fraud Data Analyst takes a data-driven approach to research, prevent and manage fraud at scale. The position will be tasked with performing intensive analyses to assess fraud risk, monitor organizational performance, and proactively mitigate fraud associated with all aspects of the member account. This position will work closely with multiple areas of the organization to research and investigate fraud incidents, leveraging data and analytics with a focus on proactively staying ahead of the fraud trends.

Responsibilities

• Work with VP of Fraud Management and Director of Fraud Prevention and Analytics to define and execute the strategic plan for the development and maintenance of fraud prevention platforms, including rules, models, and detection systems, both internally developed and with vendor partners.
• Minimize false positives and negative impacts on legitimate transactions.
• Analyze data and leverage fraud tools to identify emerging fraud risks, including but not limited to identity theft, money mule scams, and account fraud and work with multiple transaction types including debit/credit cards, checks, wires, ACH, Billpay, and Zelle.
• Key driver in the development and utilization of advanced analytics techniques (machine learning, AI, etc.) to identify, mitigate and respond in real-time to fraud patterns, emerging threats, and trends.
• Performs root cause analysis (RCA) following events and provide actionable recommendations for remediation, ensuring necessary controls are in place to prevent similar attacks in the future.
• Keep current on developments in data management, data analysis, data visualization, behavioral profiling, machine learning and artificial intelligence as it relates to fraud prevention and fraud analytics
• Collaborate with the Model Risk Management Committee (MRMC) to ensure fraud detection models are compliant, effective, and aligned with regulatory standards; contribute to model validation, performance monitoring, and risk assessments.
• Document and maintain comprehensive fraud prevention strategy, rules, model documentation, and fraud data.
• Apply descriptive statistics, inferential statistics, and regression analysis techniques to detect and analyze fraudulent transactions, leading to the development of effective fraud detection models.
• Support the creation of robust dashboards and KPIs to track fraud performance and measure the effectiveness of fraud prevention strategies.
• Proactively communicate results to Fraud leadership, the Senior Vice President responsible for Fraud Management and other executive leadership.
• Independently assess, prioritize, and deliver on projects that impact core business workstreams.
• Perform routine audits of monitoring to ensure consistent data quality and coverage.
• Leverage and enhance existing tools and processes to enable a more effective user-based threat detection and investigation program.
• Analyze fraud trends and contribute to fraud intelligence reports to enhance organizational fraud prevention strategies.
• Support the team in developing fraud KPIs and dashboards to measure fraud 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, ensuring alignment to data policies and standards.
• Perform related duties as assigned.

Requirements

• Six years’ experience in fraud prevention experience in a progressive analytics position.
• Experience in a financial fraud setting required.
• Bachelor’s degree in data analytics, statistics, business, or related field.
• Education must be from an accredited institution and education will be verified.
• Advanced skills with Microsoft Office Suite (IE. Outlook, Word, PowerPoint, and Excel)
• Experience with data visualization using Power BI and Tableau or other software
• Advanced proficiency in research, advanced statistical methods and supporting data and analysis tools (R, Python, SAS, SPSS, SQL and similar), quantitative modeling, and other applicable analytic methods (e.g., survey research, ONA).
• Advanced experience using fraud risk scoring, machine learning-based fraud detection, or SIEM tools (e.g., Splunk, ArcSight).
• Advanced knowledge of data reporting over complex data systems, including many-to-many databases and cross-server data solutions.
• Proficiency in research methodology and turning insights to action
• Demonstrated ability to clearly express ideas, methodology, results and recommendations verbally, in writing and through insightful reports and graphic illustrations
• Demonstrated ability to document outcomes and present information in a manner appropriate for key stakeholders and all levels of the organization.
• Ability to analyze data for patterns and trends and to take findings and communicate them in an effective manner
• Ability to research and make appropriate decision regarding complex cases
• Experience working in the Fraud Analytics or Investigations space within Financial Services industry
• Able to hold oneself and others accountable, provide feedback, and have tough conversations when warranted
• Experience working with various alerting and monitoring tools, navigating and reviewing system logs, and optimizing an existing process with automation
• Able to think holistically, possess curiosity, and can articulate the tradeoff actions may have between risk and impact on the customer experience
• Possess sound methodical judgment, can prioritize conflicting priorities, can derive solutions from ambiguity to meet deadlines, and is willing to take on ad-hoc projects
• Possess strong communication skills and the ability to forge partnerships with internal stakeholders through collaboration
• Able to challenge the status quo when appropriate to deliver solutions that protect Mountain America and its customers

Nice-to-haves

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

Benefits

• Friendly, comfortable and inclusive work environment
• Fun employee activities
• Exciting charity events