Fraud Strategy Associate, Brex

• Technical Mastery: Capable with SQL and/or Python for data wrangling, statistical modeling, and automation
• Industry Experience: 3+ years of experience in fraud strategy, risk operations, or data-driven business operations within a financial services or high-growth fintech environment
• Operational Mindset: Proven ability to build scalable processes and manage complex projects from data exploration through to operational rollout
• Communication: Exceptional ability to synthesize complex analytical findings into clear, executive-level strategic narratives

Desirable

• As a Fraud Strategy Associate, you’ll own the end-to-end integrity of Brex’s fraud and risk ecosystem across credit, deposit, and card payment rails
• You'll find patterns, trace root causes, and build the detection logic, automations, and reporting that keep fraud in check without adding friction for customers
• You’ll design your own solutions, see fraud across every product vertical, and partner with Risk, Data Science, Engineering, and Product to build prevention into the product itself
• Data Mining: Use SQL and Python to mine large-scale data, and apply LLM-based tools to detect and automate the identification of fraudulent patterns across credit, deposit, and card payment rails
• Vendor and Rule Optimization: Design and refine automated detection logic to proactively mitigate risk while maintaining a frictionless experience for legitimate customers
• Emerging Threat Intelligence: Stay ahead of industry trends and regulatory shifts to rapidly deploy new defensive strategies against novel fraud vectors
• Workflow Architecture: optimize the internal processes for fraud investigations, ensuring operational discipline, case visibility, and high-fidelity documentation
• Cross-Functional Collaboration: Serve as the strategic bridge between Risk Leadership, Analytics, Data Science, Engineering, and Product teams to integrate fraud-prevention infrastructure into the core product lifecycle
• Tooling & Infrastructure: Define and manage the technical requirements for internal AI-driven tools and third-party risk-reduction platforms
• KPI Management: Define and monitor key performance indicators (KPIs) such as false positive rates, fraud capture rates, and operational turnaround times
• Executive Dashboards: Build and maintain scalable reporting suites to provide real-time visibility into fraud exposure and program effectiveness for senior stakeholders
• Impact Assessment: Conduct deep-dive post-mortems on fraud incidents to quantify financial impact and recommend structural process improvements