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Quality Analyst, AI Business

Mexico, Mexico City · Job Posted January 07, 2026
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Job Description

As a Quality Analyst within Prolific AI Data Services, you will play a critical role in ensuring the consistency, reliability, and integrity of the human data we deliver to customers. As task types and volumes grow, quality can’t rely on spot checks or tribal knowledge—this role helps operationalise quality through measurement, early detection, and clear feedback loops. You’ll work closely with Operations, reviewers, and Quality and Delivery leads to run day-to-day quality measurement, surface issues early, and help turn fixes into repeatable workflows that scale across studies and customers.

Job Responsibility

  • Run day-to-day quality measurement for managed service studies, including sampling, rubric-based review, and structured reporting
  • Apply rubrics and guidelines consistently, flag ambiguities, and propose clear, actionable clarifications as task types evolve
  • Maintain and update golden sets, and support calibration efforts by preparing materials, tracking outcomes, and documenting decisions
  • Track defects and failure modes by categorising issues, assessing severity, and keeping defect taxonomies current
  • Run automated quality checks using SQL and Python or R, including completeness checks, schema and format validation, anomaly detection, and label distribution monitoring
  • Support launch gates by preparing readiness artefacts such as rubric versioning, gold status, sampling plans, and early pilot findings
  • Investigate quality drops by pulling examples, quantifying scope, and supporting root-cause analysis and corrective and preventive actions (CAPAs)
  • Build dashboards and weekly updates covering defect rates, rework, agreement, throughput versus quality trade-offs, and SLA risk
  • Partner with Operations, reviewers, and—when needed—Product and Engineering to improve task design, reviewer workflows, and escalation paths

Requirements

  • 1–3 years of experience in analysis, quality, operations, or data-focused roles, or equivalent academic projects or internships
  • A background in computer science, data science, statistics, engineering, or a related quantitative discipline
  • Strong SQL skills (required), with the ability to independently query, join, and summarise datasets to answer quality and operational questions
  • Working proficiency in Python and/or R, with experience writing scripts or notebooks to clean data, compute metrics, and automate checks
  • Strong analytical rigour, with a high bar for precision, consistency, and clear documentation of decisions
  • Solid statistical fundamentals, including intuition for sampling, distributions, confidence, and agreement concepts
  • Clear and structured communication skills, with the ability to explain issues using concrete examples and propose practical fixes
  • A collaborative mindset and willingness to partner cross-functionally to improve quality outcomes and delivery reliability

Nice to have

  • Experience with human data workflows such as annotation or data labelling, or ML/LLM evaluation (rubric-based evals, preference data, red teaming)
  • Familiarity with QA concepts such as defect severity, leakage, root-cause analysis, and CAPA processes
  • Experience building or maintaining dashboards in BI tools such as Looker, Tableau, or Mode

What we offer

  • competitive salary, benefits, and hybrid working within our impactful, mission-driven culture
  • equity
  • opportunity to earn a cash variable element, such as a bonus or commission

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