Project Perseus | Data Quality Analyst - Arabic Speakers (Human-in-the-Loop AI)

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.

What You’ll Do

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

What We’re Looking For

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

Benefits