Role Summary
DataXWorks is hiring an AI Data Quality Analyst to support dataset validation, quality assurance, and data readiness for enterprise AI and machine learning projects.
This role focuses on ensuring that AI datasets are accurate, consistent, complete, and ready for model training, evaluation, and production use.
Key Responsibilities
- Review AI datasets for quality, accuracy, consistency, completeness, and usability.
- Identify data gaps, duplicate records, formatting issues, labeling errors, and quality risks.
- Validate datasets against project requirements, schemas, guidelines, and business rules.
- Work with annotation, enrichment, and project teams to resolve data quality issues.
- Support dataset QA reports, error analysis, and quality improvement tracking.
- Assist in building data quality checklists, review frameworks, and validation workflows.
- Escalate data anomalies, edge cases, and compliance-sensitive issues.
Required Skills & Experience
- 2+ years of experience in data quality, data QA, data annotation QA, data validation, or data operations.
- Strong attention to detail and analytical thinking.
- Ability to work with structured and unstructured datasets.
- Basic understanding of AI/ML datasets, training data, or model validation workflows.
- Familiarity with Excel, Google Sheets, SQL, or data review tools is preferred.
- Good communication and documentation skills.
Why Join DataXWorks?
You will support the quality layer behind enterprise AI systems by helping teams build reliable and production-ready datasets.
