Quality Assurance Analyst

About the role

The Quality Assurance Analyst ensures the accuracy, consistency, and reliability of datasets, AI outputs, digital content, and operational workflows. You will evaluate annotated datasets, model responses, software outputs, and content deliverables against defined standards and project requirements, helping to maintain high data integrity and improve AI system reliability.

Key responsibilities

• Review datasets, AI outputs, and operational results for accuracy and completeness.
• Identify, document, and report inconsistencies, errors, and quality gaps.
• Collaborate with data operations and AI teams to implement corrective actions and quality improvements.
• Maintain QA documentation, quality‑control processes, and testing protocols.
• Develop and apply testing procedures for dataset annotation and AI output evaluation.
• Ensure compliance with project guidelines, standards, and ethical requirements.

Required profile

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Statistics, Quality Assurance or a related field.
• 3‑5 years of proven experience in QA, data validation, or analytics.
• Familiarity with QA testing methodologies and tools.
• Understanding of dataset validation, auditing, and error detection.
• Basic knowledge of AI or machine‑learning workflows (advantage).
• Relevant certifications such as Quality Assurance, QA Testing, or Data Quality/Analytics (advantage).

Required skills

• Spreadsheets (e.g., Excel)
• Databases (e.g., SQL)
• Reporting tools
• QA testing methodologies and tools
• Dataset validation techniques