Data Quality Team Lead

Are you a strategic leader who thrives at the intersection of operational excellence and high-stakes data quality? Welo Data is looking for a Data Quality Lead for Project Perseus.

This role is equal parts people leadership, quality ownership, and strategic thinking. You won’t just manage throughput—you will define how quality is measured, calibrated, and improved in one of the world’s most advanced AI evaluation environments. You are the bridge between the analysts and the stakeholders, ensuring every piece of human feedback is a step toward a smarter, safer AI.

• Strategic Oversight: Lead a team of Data Quality Analysts, aligning their daily activities with global business objectives and project milestones.
• Quality Ownership: Own the end-to-end quality loop—from identifying model performance gaps to running high-level calibrations and feedback cycles.
• Operational Architecture: Translate ambiguous or evolving AI guidelines into clear, actionable direction for your team.
• Stakeholder Partnership: Act as the primary voice of your team, partnering with technical stakeholders to align on quality standards and program expectations.
• Talent Development: Drive team growth through proactive coaching, performance management, and supporting the hiring of specialized linguistic talent.

• Job Title: Data Quality Team Lead
• Employment Type: W2 Full-Time Employee
• Hours: 40 hours per week (Full-Time)
• Status: Operational Leadership
• Pay Rate:43.50 $
• Location: New York City (On-Site)

• The Track Record: 5–8 years of experience in Data Quality, QA, or AI/ML operations, with at least 2+ years specifically leading teams at scale.
• Academic & Linguistic Foundation: Native-level English proficiency and a University Degree (Bachelor’s or higher) are mandatory.
• Multilingual Advantage: Bilingual mastery in French, Italian, German, Spanish, or Brazilian Portuguese is highly preferred.
• Operational Mindset: Proven ability to manage performance across multiple workstreams while balancing speed, quality, and shifting priorities.
• Technical Intuition: A deep interest in how human feedback shapes LLM behavior and the ability to "zoom out" to spot broad patterns in data.
• Ambiguity Mastery: Strong judgment and the ability to make high-impact decisions when guidelines are evolving or unclear.