Senior Fraud Response Data Analyst at Q2
Austin, TX — full-time
As a Senior Fraud Response Data Analyst, you will transform fraud data into actionable intelligence that strengthens fraud controls, protects customers, and supports strategic decision-making. As a key member of the Fraud Response Team, you will lead fraud trend analysis, identify emerging threats, and deliver insights that support investigations, incident response, fraud mitigation, and risk remediation efforts. You will partner closely with Product, Security, Engineering, and Customer Support teams to develop meaningful metrics, evaluate fraud detection strategies, and provide executive-level reporting. The ideal candidate combines advanced analytical expertise with a strong investigative mindset and the ability to think like an attacker. By anticipating how fraudsters may bypass controls, evade detection rules, or exploit process weaknesses, you will proactively identify vulnerabilities and recommend improvements to fraud prevention and detection capabilities. As a trusted thought leader, you will translate complex data into clear business recommendations, influence strategic priorities, and help the organization stay ahead of evolving fraud threats. RESPONSIBILITIES: Develop, maintain, and refine fraud performance metrics, KPIs, and KRIs to measure fraud losses, customer impact, control effectiveness, and fraud response performance Build and manage executive-level dashboards and reporting that provide visibility into fraud trends, emerging threats, incident activity, loss drivers, and remediation efforts Conduct deep-dive fraud analysis to identify emerging fraud schemes, attack patterns, vulnerabilities, and opportunities to improve fraud prevention and detection capabilities. Support high-profile fraud investigations by providing actionable intelligence, trend analysis, root cause insights, and data-driven recommendations. Analyze fraud losses and customer impact across banking, deposit, payment, and digital banking channels to identify systemic issues and areas of elevated risk. Evaluate fraud detection rules, models, and monitoring strategies to identify opportunities for optimization and improved performance. Apply an attacker mindset to anticipate how fraudsters may adapt to new controls, exploit process weaknesses, evade detection logic, or circumvent model thresholds. Translate complex datasets into clear and actionable insights through data visualization, executive storytelling, and strategic recommendations. Ensure data quality, accuracy, and completeness across fraud reporting tools, dashboards, and data sources. Manage data visualization tools and infrastructure, including Power BI, Excel-based models, and analytical reporting platforms. Partner with Product, Engineering, Security, and Customer Support to identify vulnerabilities, evaluate mitigation strategies, and drive fraud risk reduction initiatives. Collaborate with data scientists, engineers, analysts, and business stakeholders to develop unified fraud intelli