Mountain America Credit Union is looking to prevent and manage fraud at scale by performing intensive analyses to assess fraud risk, monitor organizational performance, and proactively mitigate fraud associated with all aspects of the member account.
Requirements
- 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.
- Certifications such as CFE (Certified Fraud Examiner), CISA, CISSP, or CEH preferred
- Experience working with various alerting and monitoring tools, navigating and reviewing system logs, and optimizing an existing process with automation
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.
- 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.
- Apply descriptive statistics, inferential statistics, and regression analysis techniques to detect and analyze fraudulent transactions, leading to the development of effective fraud detection models.
Other
- Six years’ experience in fraud prevention experience in a progressive analytics position.
- Bachelor’s degree in data analytics, statistics, business, or related field.
- 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
- Able to hold oneself and others accountable, provide feedback, and have tough conversations when warranted
- Possess strong communication skills and the ability to forge partnerships with internal stakeholders through collaboration
