Senior Fraud Strategy and Analytics Manager

Your Responsibilities

• Advanced Fraud Strategy & Analytics
• Uncover Trends: Conduct complex data analysis using SQL, Python and Feature Engineering to proactively identify emerging fraud patterns and system vulnerabilities before they impact the platform.
• Deploy Fraud Rules: Design, test, and implement robust fraud prevention rules that successfully catch bad actors while maintaining a seamless experience for real customers.
• Drive Strategy: Elevate Raisin US’s capabilities by introducing industry best practices, new methodologies, and innovative fraud prevention strategies that we aren't using today.
• KPIs & Dashboards: Build out data-driven dashboards to track fraud metrics, losses, and mitigation performance, presenting actionable findings directly to leadership.
• Model Development & Maintenance
• Build Predictive Models: Design, build, and deploy machine learning and predictive models utilizing Python to detect anomalies across the entire customer journey (onboarding, funding, and money movement).
• Feature Engineering: Develop model features based on identity, device, behavioral, and transactional data.
• Cross-Functional Delivery: Partner closely with Product and Engineering to integrate these models into our real-time production pipelines.
• AML & Financial Crime Collaboration
• Risk Profiling: Partner with the Compliance team to enhance customer risk profiling, transaction monitoring, and KYC/AML workflows.
• Design low-friction, custom risk rules for identity verification, account takeover protection, and transaction monitoring.
• Continuous Back-Testing: Routinely stress-test current rules against changing regulatory standards and evolving financial crime tactics.

Your Profile

• Financial Services Background: 8+ years of experience in fraud risk management, analytics, or financial crime specifically within fintech, retail banking, or digital payments.
• Master of Analytics: Exceptional analytical capabilities are your biggest asset. You love diving into raw data to solve complex puzzles.
• Technical Stack: Highly proficient in SQL and Python for data manipulation, analytics, and building predictive models. Experience building out fraud dashboards is a must.
• Payment System Domain Expertise: Deep understanding of Deposits and ACH is required; direct experience with modern instant payment systems like RTP and FedNow is highly preferred.
• Rule & Model Builder: Proven track record of designing custom fraud rules and deploying machine learning or statistical models in a live environment.