🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Cookies & analytics consent
We serve candidates globally, so we only activate Google Tag Manager and other analytics after you opt in. This keeps us aligned with GDPR/UK DPA, ePrivacy, LGPD, and similar rules. Essential features still run without analytics cookies.
Read how we use data in our Privacy Policy and Terms of Service.
🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Odixcity Consulting • Spain
Role & seniority: QA Analyst (Quality Assurance Analyst), mid-level with 3–5 years of QA/data validation/analytics experience
Stack/tools: QA testing methodologies/tools; spreadsheets; databases; reporting tools; basic AI/ML workflow knowledge; QA documentation systems
Review datasets, AI outputs, and operational results for accuracy
Identify, report, and track inconsistencies, errors, and quality gaps
Collaborate with data operations and AI teams to implement quality improvements; maintain QA docs and testing protocols; ensure alignment with project standards and ethics
Bachelor’s degree in Computer Science, Data Science, Information Systems, Statistics, QA or related field
3–5 years in QA, data validation, or analytics
Familiarity with QA methodologies/tools; dataset validation and error detection
Experience with spreadsheets, databases, and reporting tools
Basic knowledge of AI/ML workflows
QA or Data Quality/Analytics certifications
Additional certifications in QA/testing
Location & work type: Not specified; no location or remote/on-site instruction provided
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.