Trust and Safety Specialist

Welo Data, part of Welo Global, partners with foundation labs and enterprises to deliver multilingual data and evaluation services for generative AI systems. The company maintains a vetted network of over 500,000 experts across 300+ languages and locales, ensuring AI models perform reliably across languages, cultures, and real-world contexts. Their proprietary NIMO framework combines advanced verification, continuous monitoring, and structured quality assurance to maintain data integrity and workforce trust at global scale.

The Trust and Safety function at Welo Data protects the integrity of this distributed workforce through a multi-layered fraud detection approach. The team runs investigations combining identity verification checks, behavioral analysis, and platform activity monitoring, while building out specialized workstreams focused on identity verification, location verification, account integrity, and multi-accounting detection.

What you'll do

• Investigate flagged accounts end-to-end by triaging cases, reviewing identity signals and behavioral flags, reaching dispositions, and processing removals according to policy and service-level agreements
• Review identity and location signals for high-risk accounts, distinguishing legitimate edge cases from fraudulent activity
• Conduct manual audits and reviews prioritized by risk level and signal strength rather than intake order
• Identify multi-accounting patterns and account integrity abuse by recognizing linked accounts, device and location overlap, and behavioral signals
• Apply hypothesis-driven investigation methodology to form theories, test them against evidence, and reach reproducible, auditable dispositions
• Escalate emerging fraud patterns, false-positive and false-negative cases, and detection gaps to the fraud strategy team
• Handle sensitive data according to GDPR and equivalent privacy frameworks throughout your casework
• Work across teams including Research Labs, Quality Strategy Architecture, and Forward Deployment Engineering to address tooling gaps and process improvements

What you'll bring

• Five or more years in trust and safety, fraud and risk, or identity verification investigations at platforms, marketplaces, fintech companies, identity verification vendors, or crowdsourced workforce environments
• Hands-on experience with identity and fraud signals including device fingerprinting, IP and geolocation checks, document verification, and behavioral fraud scoring
• Demonstrated pattern recognition in multi-accounting and account integrity abuse, having worked with linked-account farming, account sharing, or similar scenarios
• Strong case documentation discipline with evidence-backed notes that withstand audit and appeal processes
• Ability to prioritize investigative queues by risk level rather than volume
• Working knowledge of data privacy regulations including GDPR as applied to case handling and data retention practices

Nice to have

• Background in AI or ML data annotation, reinforcement learning from human feedback, or research operations workforce platforms
• Experience with rule-based fraud detection engines and perspectives on rule management versus signal quality
• Conceptual familiarity with clustering or anomaly detection approaches to fraud detection
• Prior use of case management systems or ticketing and knowledge-base tools

What they offer

• Full-time remote position based in Mexico or Gurgaon
• Hands-on investigative work from day one, not policy-focused role
• Opportunity to shape fraud detection strategy at a growing AI infrastructure company