Fraud Intelligence Lead

Skills

About the Role

Build and lead a high-leverage team of Fraud Intelligence Analysts, establish investigation and reporting standards, coach analysts, allocate coverage across fraud and payments pods, lead complex investigations, support incident response and alert triage, identify attacker behavior and emerging risks, and translate findings into product, model, feature, rule, and labeling improvements.

Requirements

• 5+ years of applied fraud experience in a high-velocity environment.
• Pattern synthesis, hypothesis testing, and fraud triage experience.
• End-to-end investigations across accounts, devices, and identities.
• Post-containment incident response, post-mortems, and root cause analysis experience.
• Dark-web and grey-web investigation experience.
• Ability to assess source credibility and communicate insights to technical and non-technical audiences.
• Fluency with BI tools, anomaly detection tools, and case trackers.
• SQL for deep data querying and exploratory analysis.
• Python for scripting, prototyping, and analytical workflows.
• Graph or network analysis experience preferred.
• Familiarity with rule engines, signal gating, and large-scale monitoring systems preferred.
• Experience applying AI tools and agents to investigations preferred.
• Ability to translate fraud research into signals, rules, or labeled datasets preferred.
• Fraud certification, consumer identity, payments, risk platform, production ML, or fraud tooling experience is a plus.

Responsibilities

• Set investigation, triage, and reporting quality standards.
• Coach analysts on investigation technique, pattern synthesis, and product or model input.
• Allocate coverage across Protect, IDV, and Payments or ACH pods.
• Manage matrixed staffing and represent Fraud Intelligence in product and model planning.
• Report team health, casework trends, and emerging risks.
• Own escalations involving legal, law enforcement, or regulatory parties.
• Lead complex fraud investigations across identities, accounts, devices, and transactions.
• Support fraud operations, SEVs, and alert triage.
• Reconstruct attacker sequences and translate findings into actionable insights.
• Collaborate with Data Science, ML/AI, and Product teams on labeling, features, evaluation, and model monitoring.
• Monitor external fraud trends, adversary techniques, tooling, and emerging threats.
• Perform threat modeling and initiate research proposals.

Benefits

• Equity
• Commission
• Medical insurance
• Dental insurance
• Vision insurance
• 401(k)