AI Data Quality Analyst
Tasks
- Analyze annotation errors and trends
- Collaborate with stakeholders and annotators
- Conduct root cause analysis
- Develop quality standards and guidelines
- Identify opportunities for automation
- Maintain documentation on quality protocols
- Perform quality audits on datasets
- Propose remediation strategies
- Provide feedback for process improvements
- Report on Data Quality metrics
- Resolve edge-case annotations
- Train annotators
- Use annotation and quality control tools
Perks/Benefits
Skills/Tech-stack
AI/ML | AI/ML Pipelines | Automation | Cause analysis | Communication | Data Analysis | Data Annotation | Data Quality | Documentation | ML pipelines | Problem Solving | Python | Quality Control | Root Cause Analysis | Root cause | Statistical Analysis
Education
Roles
Regions
Countries
States
Cities
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