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Welo Data is looking for experienced, detail-oriented professionals to join our team as Data Quality Analysts. This role sits at the center of execution and quality — bridging Data Labeling Associates (DLAs) and Team Leads to ensure work is not only completed, but done right.

You'll work closely with both people and AI systems — auditing outputs, supporting day-to-day execution, and helping teams apply guidelines correctly in fast-moving, real-world scenarios. The work combines data quality, light project coordination, and hands-on training, where your ability to guide others and think critically is just as important as your own output.

Project Details

• Job Title: Data Quality Analyst
• Hiring in: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston
• Hours: Full-time, 40 hours per week
• Employment Type: W2 Full-Time Employee
• Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
• Pay Rate: $38/hour
• Contract Duration: 1-year contract with possibility of extension

Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston. Please only apply if you meet this location requirement.

• Support quality and execution across DLA teams, ensuring work meets defined standards at scale
• Audit DLA outputs and provide structured, actionable feedback to improve accuracy and consistency
• Act as the first line of support for DLAs — answering questions and helping interpret guidelines
• Help DLAs navigate ambiguity and apply evolving instructions effectively
• Support onboarding and training of new DLAs through hands-on guidance and coaching
• Monitor workflows, queues, and blockers — escalating risks and gaps to Team Leads
• Identify patterns, recurring issues, and edge cases in both human and model outputs
• Participate in calibrations, team discussions, and stakeholder syncs
• Contribute to improving guidelines, processes, and overall team performance
• Document findings and feedback in a clear, concise, and actionable way

• Native-level language proficiency and a university degree (Bachelor’s or higher).
• B2 or superior level of English.  
• 2–4 years of experience in data annotation, content quality, QA, or related fields
• Strong ability to interpret and apply complex guidelines with consistency
• Excellent attention to detail with a high bar for quality
• Ability to stay consistent while working with evolving guidelines and priorities
• Experience in AI/ML data workflows or human-in-the-loop evaluation environments
• Prior experience auditing or reviewing the work of others
• Familiarity with safety, compliance, or policy-driven content evaluation

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.