Fraud Strategy Associate in Vancouver

Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly.

Operations at Brex is the backbone of Brex's mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company.

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.

This role will be based in our Vancouver office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Strategic Analysis & Detection
• 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.
• Operational Excellence & Process Ownership
• 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.
• Metrics, Reporting & Performance
• 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.

Requirements

• 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.

Bonus Points

• Advanced Certification: Certified Fraud Examiner (CFE) designation.
• Experience with Snowflake, Salesforce, and data visualization platforms like Hex.
• Experience managing fraud risk and operational workflows for products spanning multiple geographic jurisdictions.
• Experience utilizing AI tools to enhance internal operational efficiency.

Compensation

The expected salary range for this role is $95,040 - $118,800. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity.