Job Summary
We are looking for a Data Quality Analyst – AI/ML to ensure the accuracy, consistency, completeness, and reliability of datasets used in AI/ML applications. The role involves reviewing large volumes of digital content and datasets, identifying quality issues, applying defined quality standards, and supporting continuous improvement of AI data workflows.
Key Responsibilities
- Review and evaluate text, images, videos, audio, and other digital content against defined quality standards.
- Identify inaccuracies, inconsistencies, missing information, duplicates, and other quality issues.
- Perform data validation, quality checks, and audits across large datasets.
- Apply project-specific quality guidelines, classification rules, and evaluation criteria consistently.
- Investigate recurring quality issues and identify potential root causes.
- Maintain high levels of accuracy, consistency, and productivity while working with large volumes of data.
- Conduct sample-based quality audits and report findings.
- Provide detailed feedback to internal teams to improve overall data quality.
- Track quality metrics and prepare reports on identified trends and issues.
- Collaborate with AI/ML, Data Operations, Content, and Product teams.
- Support the development and improvement of quality-control processes and SOPs.
- Ensure deliverables meet defined client and project requirements.
Required Skills
- 1–4 years of experience in Data Quality, Data Validation, Quality Assurance, Content Review, Data Operations, or AI/ML-related operations.
- Strong attention to detail and ability to identify errors in large datasets.
- Experience reviewing text, images, videos, or digital content.
- Strong analytical and problem-solving abilities.
- Ability to understand and follow detailed guidelines.
- Good communication and documentation skills.
- Proficiency in MS Excel / Google Sheets.
- Comfortable working with repetitive, detail-oriented tasks while maintaining high accuracy.
Preferred Skills
- Experience working on AI/ML, Generative AI, Computer Vision, NLP, or digital content projects.
- Experience with data quality or content quality platforms.
- Basic knowledge of SQL, Python, or data analysis is an advantage.
- Experience with quality auditing, content review, or digital operations.
