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Open nowPosted yesterday

Trust & Safety Specialist III

Welocalize35 open roles

Where
Mexico
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Your applicationOpen nowTrust & Safety Specialist IIIWelocalize · Mexico

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Welocalize postings stay open a median of 25 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted yesterday

Welocalize median: 25 days open

The posting

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Job Responsibilities:

Welo Data's Trust & Safety function protects the integrity of a global, distributed workforce that powers AI data and annotation work. We run a multi-layered fraud detection stack combining identity verification checks, in-house behavioral signals, and platform activity data, and are actively building out a Trust & Safety Committee spanning four core workstreams: identity verification, location verification, account integrity, and multi-accounting detection. This is a hands-on investigative role, not a policy-only seat — you'll be working live cases from day one.

About the Role

We're looking for a Trust & Safety Specialist, based in Mexico, to join our investigations team, working active fraud cases and supporting the broader fraud strategy program. You'll come in with real T&S, fraud/risk, or identity-verification experience from another platform, marketplace, gaming company, fintech, IDV vendor, or crowdsourced-workforce environment, and be ready to run investigations, process removals, and spot fraud patterns from week one.

  • Run investigations end-to-end: triage flagged accounts, review evidence (identity signals, behavioral flags, platform activity data), reach a disposition, and process removals in line with policy and SLA
  • Own IDV review: verify identity and location signals for flagged or high-risk accounts, distinguishing genuine edge cases from fraud
  • Conduct manual audits and reviews: prioritizing cases by risk and signal strength rather than intake order
  • Detect multi-accounting and account integrity abuse: recognize patterns across linked accounts, device/location overlap, and behavioral signals
  • Apply a hypothesis-driven investigation method: form a hypothesis, test it against the evidence, and reach a disposition that can be replicated and audited
  • Contribute to detection improvement: escalate emerging fraud vectors, false-positive/false-negative patterns, and rule gaps to the fraud strategy team
  • Handle sensitive data responsibly: apply GDPR-aligned data handling and deletion practices in every case
  • Collaborate cross-functionally: partner with Research Labs, Quality Strategy Architecture (QSA), and Forward Deployment Engineering on tooling gaps and process fixes surfaced by your casework

Additional Job Details:

What You Bring (Must-Haves)

  • 5+ years in a T&S, fraud/risk, or identity-verification investigations role — from a platform/marketplace T&S team, a fintech/payments risk team, an identity-verification vendor, or a crowdsourced/gig-workforce trust function
  • Direct experience with identity/fraud signals — device fingerprinting, IP/geolocation checks, document verification, or behavioral fraud scoring
  • Multi-accounting / account integrity pattern recognition — you've dealt with linked-account abuse, farming, or account sharing before, not just single-account review
  • Case documentation discipline — you write clean, evidence-backed case notes that would survive an audit or an appeal
  • Comfort with ambiguity and volume — you can prioritize a queue by risk, not just clear it by count
  • Working knowledge of data privacy obligations (GDPR or equivalent) as they apply to case handling and data retention/deletion

Recommended Education

  • Bachelor's degree in Criminology, Law, Criminal Justice, Cybersecurity, Information Security, Data/Computer Science, or a related field
  • Equivalent practical experience in T&S, fraud investigations, or identity verification will be considered in place of a degree
  • Relevant certifications are a plus: CFE (Certified Fraud Examiner), CAMS (Certified Anti-Money Laundering Specialist), or IDV/identity risk vendor certifications

Nice to Have

  • Experience specifically in AI/ML data annotation, RLHF, or research operations workforce platforms
  • Exposure to rule-based fraud detection engines and an opinion on rule sprawl vs. signal quality
  • Familiarity with clustering/anomaly-detection approaches to fraud (even at a conceptual level)
  • Case management system experience (any ticketing or knowledge-base tooling)
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