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🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Odixcity Consulting • Portugal
Role & seniority: QA Analyst (mid-level); 3–5 years of QA, data validation, or analytics experience
Stack/tools: QA testing methodologies and tools; spreadsheets, databases, reporting tools; basic knowledge of AI/ML workflows; QA documentation systems
Review datasets, AI outputs, and operational results for accuracy
Identify, report, and help remediate inconsistencies, errors, and quality gaps
Develop and apply testing protocols for dataset annotation and AI output evaluation; maintain QA processes and documentation; ensure compliance with guidelines and standards
Bachelor’s degree in Computer Science, Data Science, Information Systems, Statistics, QA, or related field
Familiarity with QA testing methodologies and tools
Experience with dataset validation, auditing, and error detection
Proficiency with spreadsheets, databases, and reporting tools
Certifications in Quality Assurance, Data Quality/Analytics, or related areas
Basic knowledge of AI/ML workflows
Location & work type: Location and work type not specified in the provided text
QA Analyst (Quality Assurance Analyst)
Job Summary: We are looking for a QA Analyst ensures 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 ensure they meet defined standards and project requirements. The QA Analyst will help to maintain high data integrity, reducing errors and improving AI system reliability.
Key Responsibilities
Review datasets, AI outputs, and operational results for accuracy. Identify and report inconsistencies, errors, and quality gaps. Collaborate with data operations 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 ethical requirements.
Job Requirements
Bachelor’s Degree in Computer Science, Data Science, Information Systems, Statistics, Quality Assurance or related fields Familiarity with QA testing methodologies and tools. Understanding of dataset validation, auditing, and error detection. Experience with spreadsheets, databases, and reporting tools. Basic knowledge of AI or ML workflows (advantage). Required Certifications such as Quality Assurance or QA Testing Certification, Data Quality/Analytics Certification (advantage) 3-5 years of proven experience in QA, data validation, or analytics.