AI Data QA Analyst — Datasets & Quality Assurance

Odixcity Consulting; La Réunion; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

Odixcity Consulting seeks a QA Analyst to ensure the quality, consistency, and reliability of datasets, AI outputs, digital content, and operational workflows. This role evaluates annotated datasets, AI model responses, software outputs, and content deliverables to meet defined standards and project requirements.

You will review datasets, AI outputs, and operational results for accuracy; develop testing protocols; and maintain QA documentation while collaborating with data operations and AI

Qualifications

• Bachelor’s degree in CS, DS, IS, statistics, QA or related field.
• Familiar with QA testing methodologies and tools.
• Knowledge of dataset validation, auditing, and error detection.
• Experience with spreadsheets, databases, and reporting tools.
• Basic knowledge of AI/ML workflows (advantage).
• QA or data quality analytics certifications (advantage).
• 3–5 years of proven QA, data validation, or analytics experience.

Responsabilités

• Review datasets, AI outputs, and results for accuracy.
• Identify and report inconsistencies, errors, and quality gaps.
• Collaborate with data ops and AI teams to implement quality improvements.
• Maintain QA documentation and quality control processes.
• Develop and apply testing protocols for dataset annotation and AI output evaluation.
• Ensure compliance with project guidelines, standards, and ethics.

Connaissances

QA methodologies

Data auditing

Reporting tools

AI/ML workflows

Formation

BSc in CS/DS/IS/Statistics/QA

QA Certification

Outils

SQL

Excel

Description du poste

Odixcity Consulting seeks a QA Analyst to ensure the quality, consistency, and reliability of datasets, AI outputs, digital content, and operational workflows. This role evaluates annotated datasets, AI model responses, software outputs, and content deliverables to meet defined standards and project requirements.

You will review datasets, AI outputs, and operational results for accuracy; develop testing protocols; and maintain QA documentation while collaborating with data operations and AI