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Plaid

Connects financial accounts to apps and payments

Fraud Intelligence Analyst

Financial Crime & AMLConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAHybrid

About the Job

Requirements

  • At least 5 years of applied fraud experience in a high-velocity environment such as fintech, consumer payments, banking, SaaS, marketplace risk, or security research.
  • Demonstrate an investigator mindset, including pattern synthesis, hypothesis testing, and skilled triage between signal and noise.
  • Have end-to-end investigation experience reconstructing attacker intent and behavior in multi-step attack sequences across accounts, devices, and identities.
  • Have post-containment incident response experience with a deep emphasis on post-mortems and root cause analysis.
  • Have experience navigating and investigating dark and grey web sources, assessing source credibility, and translating external intelligence into actionable insights.
  • Be able to explain complex, ambiguous behavior to technical and non-technical audiences.
  • Be fluent with data environments and investigative toolchains, including business intelligence tools, anomaly detection, and case trackers.

Responsibilities

  • 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.
  • Use fraud tooling, including 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.
  • Identify gaps in internal fraud tooling and automation and drive 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 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, including entity linkages, temporal patterns, attack rotations, and tool chains.
  • Experiment with network/graph analysis, sequence mining, anomaly detection, and custom heuristics where off-the-shelf approaches fail.
  • Survey external fraud trends, adversary techniques, tooling, and emerging threat vectors.
  • Perform threat modeling of abuse surfaces and initiate research proposals when patterns emerge.
  • Produce 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.
  • Capture lessons from fraud incidents and feed them back into defenses.

Desired Qualifications

  • Use SQL for deep data querying and exploratory analysis.
  • Use Python for scripting, rapid prototyping, and analytical workflows.
  • Have graph/network analysis experience to detect linked behavioral structures or actor networks.
  • Be familiar with rule engines, signal gating, and large-scale monitoring systems.
  • Have experience applying AI tools and agents to accelerate investigations and research workflows.
  • Be able to translate fraud research into actionable signals, rules, or labeled datasets that improve model performance.
  • Hold fraud domain certifications such as CFE.
  • Have prior work on consumer identity, payments, or risk platform development.
  • Have exposure to production machine learning model lifecycles and metrics for drift/decay.
  • Have experience improving internal fraud tooling, automation, or case management systems.

About the Company

Plaid

Connects financial accounts to apps and payments

Plaid sells financial data and payment tools that businesses integrate into their apps and services. Its software lets people connect bank accounts and share selected information with financial products, while developers use APIs to retrieve account balances and transaction details. Businesses use this infrastructure to verify customers, assess borrowing capacity and move money between bank accounts, with tools that support financial apps, lenders and other organizations. Plaid charges business customers through account-based fees, subscriptions or fees for successful API requests, depending on the product and contract. Founded in 2013, Plaid is headquartered in San Francisco, California.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$1.3B
Headquarters
San Francisco, CA
Founded
2013

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