Plaid28.04.2026
Fraud Researcher
Полная занятостьУдалёнка
Обязанности
- 01Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces
- 02Provide support to day-to-day fraud operations including SEVs and alert triage
- 03Reconstruct attacker sequences and hypothesize actor intent and tooling
- 04Distill patterns from noisy signals into clear narratives and actionable insights
- 05Bridge investigation outcomes to product and model improvements
- 06Operate across Plaid's fraud tooling — dashboards, alerting systems, network signals, and analytics platforms — to detect and validate anomalies
- 07Stress-test existing capabilities, identify systemic gaps, and define new detection primitives
- 08Proactively identify gaps in internal fraud tooling and automation, driving enhancements to improve efficiency and scale
- 09Collaborate with Data Science, ML/AI, and Product teams to improve labeling, feature sets, evaluation frameworks, and model decay monitoring
- 10Surface data quality limitations and systematically formalize missing features
- 11Translate exploratory research into reusable feature pipelines, model inputs, or rule augmentations
- 12Participate in product discovery, roadmap planning, and post-launch evaluation to ensure fraud-awareness by design
- 13Conduct longitudinal and structural analysis of how fraud types manifest in Plaid network data
- 14Experiment with network/graph analysis, sequence mining, anomaly detection, and custom heuristics
- 15Continuously survey external fraud trends, adversary techniques, tooling, and emerging threat vectors
- 16Proactively perform threat modeling of abuse surfaces and initiate research proposals when patterns emerge
- 17Produce clear, evidence-backed technical reports and case studies for product, engineering, operations, legal, and executive stakeholders
- 18Document investigation workflows, attack classifications, and proof-of-concept detection logic
- 19Drive post-incident learning by capturing lessons from fraud incidents and feeding them back into defenses
Требования
- 013+ years of applied fraud experience in fintech, consumer payments, banking, SaaS, marketplace risk, or security research
- 02Investigator mindset with pattern synthesis, hypothesis testing, and signal-to-noise triage
- 03End-to-end investigation experience reconstructing attacker intent across accounts, devices, and identities
- 04Post-containment incident response experience with focus on post-mortems and root cause analysis
- 05Experience navigating dark and grey web, assessing source credibility, and translating intelligence into actionable insights
- 06Strong communication skills for explaining complex behavior to technical and non-technical audiences
- 07Tool fluency with data environments and investigative toolchains such as BI tools, anomaly detection, and case trackers
- 08Preferred: SQL for deep data querying and exploratory analysis
- 09Preferred: Python for scripting, rapid prototyping, and analytical workflows
- 10Preferred: Graph/network analysis experience to detect linked behavioral structures or actor networks
- 11Preferred: Familiarity with rule engines, signal gating, and large‑scale monitoring systems
- 12Preferred: Experience applying AI tools and agents to accelerate investigations and research workflows
- 13Nice to have: Fraud domain certifications (e.g., CFE)
- 14Nice to have: Experience with consumer identity, payments, or risk platform development
- 15Nice to have: Exposure to production ML model lifecycles and metrics for drift/decay
- 16Nice to have: Experience improving internal fraud tooling, automation, or case management systems