Hybrid Quality Analyst – Generative AI Data Quality

at Welocalize

• Job title: Quality Analyst – Generative AI Data Quality
• Job type: Full Time
• Experience level: Junior, Mid level
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: ETL, RPA
• Location requirements: Hybrid, Gurgaon, India

About the role

• Quality Analyst managing client-specific quality programs in data quality. Overseeing performance metrics and cross-functional coordination for generative AI projects.

Responsibilities

• Owns client-specific quality programs, performance metrics, and escalations while leading team development and cross-functional coordination.
• 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.

Requirements

• 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).
• 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.
• 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.