Quality Analyst - Generative AI Data Quality

Key Responsibilities

• Set client QA strategies (sampling design, audit methods, acceptance thresholds) and adapt to scope/volume changes. 
• Run root-cause analyses; drive CAPA plans with owners, timelines, and effectiveness checks. 
• Plan training & certification for raters/annotators and coordinators; track completion and impact. 
• Maintain dashboards (throughput, accuracy, productivity, cost) and convert insights into actions. 
• Manage client escalations; present options, trade-offs, and recovery paths. 
• Standardize SOPs, templates, and checklists; remove bottlenecks. 
• Pilot small automations (macros, templates, RPA/API handoffs) with Ops Tech; scale wins. 
• Coach P1s and C2–C3 on tools, workflows, and QA craft. 
• Ensure compliance/security across data handling and platform access. 

Skills

• Multi-project planning and stakeholder management. 
• Clear client communications and governance cadence participation. 
• Strong spreadsheets, PM/task boards, and basic BI; ETL familiarity is a plus. 
• Capacity planning with vendors; confident escalation/negotiation. 
• Effective in global, distributed teams. 

Additional Qualifications

• Near-native English with strong writing and editorial skills. 
• Hands-on with generative AI tools (text/voice/video). 
• Background in QA testing, rubric design, or AI safety/ethics evaluation. 
• Familiarity with data-annotation platforms and model-evaluation tools. 
• Ability to interpret code/datasets/workflows at a conceptual level (no coding required). 
• Works independently and manages workflows effectively in a remote setup. 
• Multilingual ability beyond English. 

Scope and Autonomy

• Leads quality, training, and performance tracks across several projects; independent within guardrails. 
• Shared accountability for client results and team performance with Ops Manager. 

Education and Experience

• Bachelor’s degree or equivalent experience in Business, Operations, Quality, or Data/Engineering. 
• 2+ years in quality/ops with hands-on QA and workforce/training coordination. 
• 1+ years leading people/pods (formal or informal).