Senior Fraud Research Analyst
Plaid is a financial technology company providing APIs and network connectivity for businesses to build financial products. Its platform supports bank-account linking, financial data access, identity verification, fraud and risk tools, credit underwriting, and bank payments.
Maintainer signals as of 8/12/2026
Funding history
Projects
About Plaid
Plaid operates a financial data network and API platform that lets businesses connect to financial institutions and build financial experiences. Its products support account and identity verification, real-time balance and transaction data, investment and liability data, income and underwriting workflows, fraud and AML risk checks, and multi-rail bank payments. It serves developers, businesses, financial institutions, platforms, lenders, banks, and consumer-facing financial-product providers.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead complex fraud investigations across identities, accounts, devices, and transactions; reconstruct attacker behavior; identify patterns and detection gaps; collaborate with data science, machine learning, and product teams; conduct applied fraud research; and produce technical reports and case studies.
Requirements
- 3+ years of applied fraud experience
- Experience reconstructing multi-step attacks across accounts, devices, and identities
- Post-containment incident response and root cause analysis experience
- Dark-web and grey-web investigation experience
- Strong communication skills
- Experience with data environments and investigative toolchains
- SQL
- Python
- Graph or network analysis experience
- Familiarity with rule engines, signal gating, and monitoring systems
Responsibilities
- Lead investigations into complex fraud cases
- Support fraud operations, SEVs, and alert triage
- Reconstruct attacker sequences and hypothesize actor intent and tooling
- Distill noisy signals into actionable insights
- Identify gaps in fraud tooling and automation
- Collaborate with data science, ML, and product teams on labels, features, and models
- Conduct longitudinal and structural fraud analysis
- Monitor external fraud trends and adversary techniques
- Produce technical reports and case studies
- Document investigation workflows and detection logic
Benefits
- Equity
- Commission
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k)