Lead Fraud Operations Analyst

• Lead Fraud Operations and Investigations
• Act as the primary escalation point for complex fraud and abuse investigations across Apollo’s ecosystem
• Perform root-cause analysis of new exploit behaviors, account takeovers, transactions, and scaled abuse events using data queries (SQL, Python), system logs and testing
• Conduct forensic investigations into fraud model classifications, rule bypasses, and external abuse tool behaviors
• Build and maintain investigation frameworks that allow rapid detection and classification of fraud patterns
• Develop and Optimize Fraud Detection Systems
• Configure, tune, and evaluate rules-based and model-driven fraud detection systems (e.g., Stripe Radar, Signified, or internal models)
• Collaborate with Engineering to enhance fraud detection logic and event pipelines
• identify and close systemic gaps through code- or model-level feedback loops
• Use Cursor or equivalent AI-assisted dev tools to review Ruby-based backend logic, reverse-engineer fraud actor patterns, and suggest mitigations
• Design data instrumentation for new product surfaces to improve visibility and prevention efficacy
• Cross-Team Coordination and Incident Management
• Partner with Product, Engineering, and Security to define and operationalize incident handling and postmortem processes for fraud-related events
• Lead cross-functional response efforts for fraud spikes or payment performance degradations
• Serve as a bridge between Customer Support and Technical Teams—ensuring operational processes are consistent, automated, and scalable
• Mentorship and Enablement
• Train and coach Fraud Analysts, Support, and Billing teams in investigative methods and data literacy
• Design KYC/KYB verification workflows that balance customer experience and risk control
• Create and maintain documentation, playbooks, and knowledge bases for fraud and abuse response

• 5+ years of experience in fraud operations, trust & safety, or security operations roles
• Strong SQL proficiency (joins, CTEs, aggregates)
• familiarity with Python and data visualization tools
• Experience reviewing or debugging application code (Ruby preferred), using tools like Cursor, GitHub Copilot, or IDEs for root-cause exploration
• Familiarity with payment systems (chargebacks, disputes, ACH) and the associated fraud lifecycle
• Understanding of fraud detection models and risk-scoring logic
• experience configuring or auditing rule-based systems
• Demonstrated ability to lead investigations independently, prioritize in ambiguity, and deliver results across multiple teams
• Exceptional written and verbal communication skills
• capable of translating technical detail into operational action
• Comfortable working remotely in a fast-paced, data-driven, and highly collaborative environment

Exposure to threat intelligence, OSINT, or brand abuse takedown workflows a plus

• equity
• company bonus or sales commissions/bonuses
• 401(k) plan
• at least 10 paid holidays per year, flex PTO, and parental leave
• employee assistance program and wellbeing benefits
• global travel coverage
• life/AD&D/STD/LTD insurance
• FSA/HSA and medical, dental, and vision benefits