Sr. Fraud Analyst

Responsibilities

• Manage fraud rule sets and controls, including setup and continuous performance monitoring.
• Utilize data analytics to refine rules, reduce false positives, design new rules for emerging fraud patterns, and detect suspicious activity.
• Identify and remedy control gaps.
• Influence architecture builds and data integration; orchestrate fraud monitoring across the full customer journey (payment rails, funding flows, logins, behavioral signals).
• Strengthen case management processes.
• Partner with Engineering for data harvesting, analytics, and rule implementation.
• Lead cross-functional projects from problem definition through implementation and post-mortem.
• Identify, implement, and assess vendor solutions.
• Own customer risk and KYC models: maintain and enhance customer risk rating, signup, and related fraud scoring models.
• Define model performance metrics (e.g., detection rate, false positive rate, lift) and monitor for drift.
• Partner with Customer Experience team to identify friction points, customer abandonment, and true cost of fraud prevention; reduce account locks, enable faster money movements, lower ID request rates without increasing fraud; increase greenlight passes while maintaining controls.
• Build monitoring and reporting: partner with Data/Analytics to create dashboards for fraud KPIs, trends, model health, and control coverage.
• Create recurring reporting packages for leadership, translating complex analysis into recommendations.

Requirements

• 3–5+ years in fraud prevention, analytics, and financial crime (fintech, banking, brokerage, or payments).
• Direct experience with fraud patterns/controls (e.g., ATO, ACH/transfer, card fraud, KYC/KYB, synthetic identities).
• Advanced SQL required.
• Comfortable framing analytical questions, designing experiments, and interpreting model/rule performance.
• Familiarity with the fraud ecosystem (solutions, capabilities, challenges).
• Understands fraud stack components (risk models, rules, signals); able to design monitoring for model drift, data quality, and control failures.
• Knowledge of KYC/AML, customer risk rating, and step-up auth/verification.
• Excellent communication skills; can translate complex analytics and risk trade-offs to technical and non-technical audiences.
• Comfortable presenting to senior stakeholders and committees.
• Demonstrated end-to-end project management skills.
• Collaborative; enjoys cross-functional problem-solving (Ops, Data, Eng, Compliance, Product).
• Balances fraud loss, customer experience, and efficiency.
• Stays current on emerging fraud trends and brings new ideas.

Nice-to-Haves

• Experience leading cross-functional projects.
• Knowledge of vendor solutions in the fraud space.
• Ability to influence architecture and data integration decisions.

Compensation

• Base salary: $135,000 - $160,000 (New York City).
• Eligible for variable compensation in the form of a company incentive bonus.
• Competitive benefits including medical, dental, vision; life/AD&D insurance; disability; infertility and transgender health benefits; EAP; transit benefits; FSA/HSA.
• Equity grants for all employees.
• Flexible PTO, paid parental leave, sabbatical.
• 401(k) match, student loan matching.
• Professional coaching.