Fraud Intelligence Lead

Responsibilities

Team Building & People Leadership

• Set the casework quality bar by defining rigorous investigation, triage, and reporting standards.
• Coach analysts on investigation techniques, pattern synthesis, and translating findings into product and model inputs.

Operating Model & Cross-PA Partnership

• Own coverage allocation across Protect/IDV and Payments/ACH pods, flexing assignments as volume shifts.
• Manage matrixed staffing and time allocation between the Fraud PA and Payments PA.
• Represent Fraud Intelligence in product and model roadmap discussions, translating casework patterns into strategic priorities.

Reporting & Escalation

• Report team health, casework trends, and emerging risks to the Head of Fraud.
• Own escalation paths for SEVs and incidents requiring legal, law-enforcement, or regulatory involvement.

Live Fraud Investigation & Reconstruction

• Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces.
• Support day-to-day fraud operations, including SEVs and alert triage.
• Reconstruct attacker sequences and hypothesize actor intent and tooling.
• Distill patterns from noisy signals into clear narratives and actionable insights.
• Bridge investigation outcomes to product and model improvements.

Product & Model Partnership

• Collaborate with Data Science, ML/AI, and Product teams to improve labeling, feature sets, evaluation frameworks, and model decay monitoring.
• Surface data-quality limitations and formalize missing features.
• Translate exploratory research into reusable feature pipelines, model inputs, or rule augmentations.
• Participate in product discovery, roadmap planning, and post-launch evaluation to ensure fraud awareness by design.

Ecosystem Monitoring & Knowledge Leadership

• Monitor external fraud trends, adversary techniques, tooling, and emerging threat vectors.
• Perform threat modeling of abuse surfaces and initiate research proposals when patterns emerge.

Requirements

• 5+ years of applied fraud experience in a high-velocity environment such as fintech, consumer payments, banking, SaaS, marketplace risk, or security research.
• Investigator mindset, including pattern synthesis, hypothesis testing, and skilled triage between signal and noise.
• End-to-end investigation experience reconstructing attacker intent and behavior in multi-step attack sequences across accounts, devices, and identities.
• Post-containment incident response experience with emphasis on post-mortems and root-cause analysis.
• Dark- and grey-web navigation and investigation experience, including assessing source credibility and translating external intelligence into actionable insights.
• Strong communication skills for explaining complex, ambiguous behavior to technical and non-technical audiences.
• Fluency with data environments and investigative toolchains, including BI tools, anomaly detection, and case trackers.
• SQL for deep data querying and exploratory analysis.
• Python for scripting, rapid prototyping, and analytical workflows.

Nice-to-Haves

• Graph or network analysis experience for detecting linked behavioral structures or actor networks.
• Familiarity with rule engines, signal gating, and large-scale monitoring systems.
• Experience applying AI tools and agents to accelerate investigations and research workflows.
• Ability to translate fraud research into actionable signals, rules, or labeled datasets that improve model performance.
• Fraud-domain certification such as CFE.
• Prior work on consumer identity, payments, or risk platform development.
• Exposure to production ML model lifecycles and metrics for drift or decay.
• Experience improving internal fraud tooling, automation, or case-management systems.

Compensation & Benefits

• Annual salary range: $148,800–$232,800 USD.
• Additional compensation may include equity and/or commission, depending on the position offered.
• Comprehensive benefits include medical, dental, vision, and 401(k).