Project Perseus | Data Quality Analyst - Portuguese (Portugal) Speakers (Human-in-the-Loop AI)
$38 per hourWelocalize
Data Quality Analyst
Welo Data is looking for experienced, detail-oriented professionals to join our team. 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
- Paid Vacation: 6 days
- Paid Company Holidays: 2 days (Memorial Day and Labor Day)
- Paid Sick Leave: accrued per applicable state law and company policy
- Medical, Dental, and Vision Insurance (eligibility applies)
- Health Savings Account (HSA)
- 401(k) Retirement Plan
- Employee Assistance Program
- Additional voluntary benefits (life, accident, critical illness, etc.)
- Free Gourmet Food: Free breakfast, lunch, and dinner are provided, featuring a wide variety of cuisines in multiple cafes.
- Micro-kitchens & Snacks: Offices are stocked with free snacks and beverages, including premium coffee and La Croix.
- Unique Campus Features: Some locations include roof-top nature parks
- Commuter Benefits: Free transport, shuttles, and sometimes bike-to-work perks.
$38 - $38 an hour Why This Role This is an opportunity to move beyond traditional data work and play a direct role in how AI systems are evaluated and improved. The work is fast-moving, collaborative, and increasingly central to how modern AI systems are built and deployed.
To know more details
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