Data Quality Analyst – AI/ML

Innodata India Private Limited; Guntur District; On-site; INR 600,000 - 900,000; Full time

Job summary

Innodata India Private Limited is seeking a Data Quality Analyst - AI/ML to ensure accuracy, consistency, and reliability of datasets used in AI workflows. You will review large volumes of digital content and apply defined quality standards.

You will collaborate with AI/ML and Content teams, perform data validation and audits, and contribute to improving quality-control processes and SOPs. The role emphasizes attention to detail, documentation, and the ability to follow complex guidelines.

Qualifications

• 1–4 years of experience in data quality, data validation, QA, or AI/ML-related operations.
• Strong attention to detail and the 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.
• Proficiency in MS Excel / Google Sheets.

Responsibilities

• Review and evaluate text, images, videos, 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.
• Investigate recurring quality issues and identify potential root causes.
• Maintain high levels of accuracy, consistency, and productivity.
• 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.

Skills

Data quality

Data validation

Quality assurance

Content review

Data operations

AI/ML

Job description

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.