Trust and Safety Specialist

• Run end-to-end investigations by triaging flagged accounts, reviewing identity signals, behavioral flags, and platform activity data, reaching dispositions, and processing removals according to policy and SLA
• Own identity-verification reviews for flagged or high-risk accounts, including verification of identity and location signals
• Conduct manual audits and reviews, prioritizing cases by risk and signal strength
• Detect multi-accounting and account-integrity abuse using linked-account, device, location, and behavioral patterns
• Apply hypothesis-driven investigation methods and produce replicable, auditable dispositions
• Escalate emerging fraud vectors, false-positive/false-negative patterns, and rule gaps to the fraud strategy team
• Handle sensitive data using GDPR-aligned data handling and deletion practices
• Collaborate with Research Labs, Quality Strategy Architecture, and Forward Deployment Engineering on tooling gaps and process improvements

• 4+ years in a T&S, fraud/risk, or identity-verification investigations role
• Direct experience with identity/fraud signals, including device fingerprinting, IP/geolocation checks, document verification, or behavioral fraud scoring
• Experience recognizing multi-accounting/account integrity patterns, linked-account abuse, farming, or account sharing
• Strong case documentation discipline with clean, evidence-backed case notes
• Ability to prioritize investigation queues by risk and signal strength
• Working knowledge of GDPR or equivalent data privacy obligations for case handling and data retention/deletion
• Bachelor's degree in Criminology, Law, Criminal Justice, Cybersecurity, Information Security, Data/Computer Science, or a related field, or equivalent practical experience in T&S, fraud investigations, or identity verification
• Relevant certifications are a plus: CFE, CAMS, or IDV/identity risk vendor certifications
• Nice-to-have: experience in AI/ML data annotation, RLHF, or research operations workforce platforms
• Nice-to-have: exposure to rule-based fraud detection engines
• Nice-to-have: familiarity with clustering/anomaly-detection approaches to fraud
• Nice-to-have: case management system experience
• Must be based in India