Fraud and Abuse Operations Analyst

Plaid•San Francisco, CA

1d•$138,000 - $163,200

About The Position

We are the first line of defense against fraud and abuse on the Plaid platform. Our mission is to ensure the safety and integrity of our platform for consumers and customers. As a Fraud and Abuse Operations Analyst, you will be responsible for responding to fraud and abuse events, investigating claims, and triaging incidents. We also partner with product and engineering teams to inform and improve fraud mitigation strategies.

Requirements

3+ years of experience in fraud/abuse operations, trust & safety, and/or incident response
Experience triaging fraud or related incidents, with tight containment deadlines.
Experience managing escalations and making informed trade-off decisions with multiple stakeholders.
Ability to coordinate and communicate effectively with internal Legal, Compliance, Comms and other risk management teams during incident triage.
A battle-tested mental model for balancing fraud mitigation vs. conversion, and the ability to calibrate and apply this mental model in the context of Plaid’s business objectives under pressure.
Working knowledge of fraud typologies–account takeover, different types of payments fraud, ACH fraud, chargebacks, kiting, rewards harvesting, etc.
Familiarity with the tactics, techniques, and procedures (TTPs) used by bad actors to commit different types of fraud on the web.
Familiarity with common mitigation strategies for the same, with a developing point of view on their relative pros and cons.
Dark and grey-web navigation and investigation experience, ability to assess source credibility, and translate external intelligence into actionable insights.
Experience translating fraud investigations and research into actionable detection signals, rules, and labeled datasets, while partnering closely with DS/ML and product teams to improve feature sets, labeling quality, evaluation frameworks, and model decay monitoring.
Experience developing and maintaining threat models for authentication and other high-risk product surfaces, with a track record of proactively identifying emerging risks.
Proficiency with SQL for querying data sets and building reports.
Comfortable with common analysis tools and manipulation tools.
Ability to spot anomalies and fraudulent patterns in logs and other data sets (transactions, request data, etc.), with judgment to escalate ambiguous cases.
Experience contributing improvements to operational processes and controls.
Strong written and verbal communication skills.

Nice To Haves

Familiarity with machine learning models for fraud detection.
Fraud domain certifications (e.g., CFE/fraud examination background).
Exposure to production ML model lifecycles and metrics for drift/decay.
Effective use of AI and AI agents to accelerate investigations and research

Responsibilities

Participate in the abuse on-call rotation, directly protecting our users and customers by responding to and resolving fraud and abuse events.
Investigate fraud and abuse claims from diverse sources, partnering with senior teammates on complex cases.
Proactively perform threat modeling of abuse surfaces and continuously survey external fraud trends, adversary techniques, tooling, and emerging threat vectors.
Help triage and manage fraud and abuse events as internal incidents (SEVs), collaborating across teams to drive resolution.
Partner with Consumer Risk and other product teams, providing operational insights from on-call and investigations.