Review suspicious activity flagged by fraud systems and mitigate to protect users.
Use AI tools to enhance fraud detection and operational productivity.
Collaborate with Product, Engineering, and vendors to design/test tooling for evolving fraud.
Identify new fraud trends and present data-informed guardrails.
Handle daily fraud escalations with Data Science, Engineering, and Product to build risk frameworks.
Support Revenue Protection leadership with policies, automation, and playbooks.

🎯 Requirements

2+ years in fraud analysis or revenue protection.
Knowledge of fraud prevention, disputes, and financial crime risks.
ML and rule-based fraud tooling experience (Ravelin, Sift, Signifyd, Accertify).
Data skills: SQL; BigQuery; Looker/Tableau.
Analytical, independent thinker who handles ambiguity.
Collaborative communicator with internal stakeholders.

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