Senior Fraud Research Analyst

Plaid

Senior Fraud Researcher leading complex investigations into fraud cases at Plaid. Collaborating with data science and product teams to enhance fraud detection.

Posted 7/28/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $139,000 - $191,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in fraud investigation, including the ability to reconstruct attack sequences and synthesize patterns from complex data. Proficient in collaborating with cross-functional teams to enhance fraud detection capabilities and improve operational efficiency.

Highest-signal resume keywords

Fraud Investigation ExperiencePattern SynthesisPost-Mortem AnalysisAnomaly DetectionData Environment Tool Fluency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Fraud AnalysisIncident ResponseRoot Cause AnalysisHypothesis TestingMulti-Step Attack Reconstruction

Soft Skills

Investigator MindsetCollaborationCommunication

Tools & Technologies

BI ToolsAnomaly Detection ToolsCase TrackersFraud ToolingAnalytics Platforms

Industry Keywords

FintechConsumer PaymentsBankingMarketplace RiskSecurity Research

About the role

Key responsibilities & impact

Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces
Provide support to 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
Operate across Plaid's fraud tooling — dashboards, alerting systems, network signals, and analytics platforms — to detect and validate anomalies
Stress-test existing capabilities, identify systemic gaps, and define new detection primitives
Proactively identify gaps in internal fraud tooling and automation, driving enhancements to improve efficiency and scale
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 systematically 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
Conduct longitudinal and structural analysis of how fraud types manifest in Plaid network data — entity linkages, temporal patterns, attack rotations, tool chains
Experiment with network/graph analysis, sequence mining, anomaly detection, and custom heuristics where off-the-shelf approaches fail
Continuously survey external fraud trends, adversary techniques, tooling, and emerging threat vectors
Proactively perform threat modeling of abuse surfaces and initiate research proposals when patterns emerge
Produce clear, evidence-backed technical reports and case studies for product, engineering, operations, legal, and executive stakeholders
Document investigation workflows, attack classifications, and proof-of-concept detection logic
Drive post-incident learning by capturing lessons from fraud incidents and feeding them back into defenses

Requirements

What you’ll need

3+ years of applied fraud experience in a high-velocity environment (fintech, consumer payments, banking, SaaS, marketplace risk, or security research)
Investigator mindset: 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 a deep emphasis on post-mortems and root cause analysis
Dark and grey-web navigation and investigation experience; ability to assess source credibility and translate external intelligence into actionable insights
Tool fluency with data environments and investigative toolchains (BI tools, anomaly detection, case trackers)

Benefits

Comp & perks

Comprehensive benefit plan, including medical, dental, vision, and 401(k)