Senior Quality Analayst, AI Data Quality

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• Own portfolio-level QA frameworks and rubrics; keep alignment across programs and regions.
• Lead automation and tooling roadmap with Ops Tech/Product (templates, scripts, API/RPA pilots).
• Run systemic RCAs across programs; set cross-cutting corrective actions with measurable outcomes.
• Design enablement programs (bootcamps, certification paths) and evaluate effectiveness.
• Champion data quality metrics; define thresholds and guidance for model training/eval tasks.
• Lead client/exec reviews on quality; translate insights into roadmap and investments.
• Mentor P2/P1; guide C2–C3 growth in quality craft and reporting standards.
• Ensure audit readiness and drive continuous improvement culture. Additional Job Details: Education
• Bachelor’s degree or equivalent experience in Business, Operations, Quality, or Data/Engineering. Experience - 2–3 years in quality/ops; 2+ years leading managers/pods or complex workstreams. Skills
• Portfolio planning and governance; financial awareness.
• Executive-ready communication; strong negotiation.
• Advanced analysis (spreadsheets, BI); SQL/ETL familiarity a plus.
• Change leadership, standardization, and automation at scale. Additional Qualifications (P1+)
• 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 & Autonomy
• Owns outcomes for a portfolio of quality programs; sets methods and standards.
• Works independently; escalates only non-standard/high-impact items.
• Joint planning with Sr. Ops Manager for quality and client outcomes.