Fraud Researcher
Job
Plaid
New York, NY (In Person)
$238,800 Salary, Full-Time
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Job Description
Fraud Researcher Plaid
- 4.3 New York, NY Job Details Full-time $190,800
- $286,800 a year 17 hours ago Qualifications Report writing SQL databases Hypothesis testing Automation Product roadmapping Certified Fraud Examiner Technical report writing 3 years SQL Pattern recognition Financial fraud investigation Analysis skills Incident response Outlier detection Bank experience Root cause analysis Data analytics tools Case studies Senior level SaaS AI Leadership Communication skills Python Stress Testing Full Job Description We believe that the way people interact with their finances will drastically improve in the next few years.
Responsibilities:
Live Fraud Investigation & Reconstruction 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 Signal & Tool Utilization at Scale 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 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 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 Deep Applied Fraud Research 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 Ecosystem Monitoring & Knowledge Leadership 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 Case Studies & Reporting 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 defensesQualifications:
Required 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 Strong communication: ability to explain complex, ambiguous behavior to technical and non-technical audiences Tool fluency with data environments and investigative toolchains (BI tools, anomaly detection, case trackers) Preferred SQL for deep data querying and exploratory analysis Python for scripting, rapid prototyping, and analytical workflows Graph/network analysis experience to detect 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 Nice to Have Fraud domain certifications (e.g., CFE) Prior work on consumer identity, payments, or risk platform development Exposure to production ML model lifecycles and metrics for drift/decay Experience improving internal fraud tooling, automation, or case management systems $190,800- $286,800 a year The target base salary for this position ranges from $190,800 year to $286,800/year in Zone 1. The target base salary will vary based on the job's location. Our geographic zones are as follows: Zone 1
- San Francisco / New York City / Seattle Zone 2
- Los Angeles / Washington DC / Austin / Boston / Sacramento / San Diego Zone 3
- Atlanta / Portland / Chicago / Philadelphia / Denver / Miami / Dallas / Raleigh Zone 4
- All other US cities The base salary range listed for this full-time position excludes commission (if applicable), equity and benefits.
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