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1 week ago
We're seeking a detail-driven professional to ensure the accuracy and quality of client data. As an AI Data Quality Analyst, you'll play a pivotal role in guaranteeing exceptional results.
Key Responsibilities:- Quality Audits: Conduct thorough examinations of annotated datasets to ensure compliance with established guidelines and quality benchmarks.
- Statistical Reporting: Utilize statistical metrics such as F1 score and inter-annotator agreement to evaluate data quality and pinpoint areas for enhancement.
- Root Cause Analysis: Analyze annotation errors, trends, project processes, and documentation to identify the root cause of errors and propose effective mitigation strategies.
- Edge-Case Management: Resolve and analyze edge-case annotations to guarantee quality and identify opportunities for optimization.
- Automation: Identify automation opportunities to enhance analytics, provide deeper insights, and boost efficiency.
- Documentation: Develop and maintain up-to-date documentation on quality standards, annotation guidelines, and quality control procedures.
- Feedback: Provide regular feedback highlighting areas for improvement across the annotation pipeline.
- Cross-Functional Teamwork: Collaborate closely with key stakeholders and clients to understand project requirements and improve annotation pipelines.
- Training: Assist with training annotators, providing guidance, feedback, and support to ensure data quality.
- Reporting: Deliver regular updates showcasing data quality metrics, key findings, and actionable insights for continuous process enhancements.
- 1+ years of experience as a data analyst with exposure to data quality and/or data annotation, preferably within an AI/ML context.
- Familiarity with basic AI/ML concepts and data principles.
- Strong analytical and problem-solving skills with an exceptional eye for detail.
- Excellent written and verbal communication skills, with the ability to articulate quality issues and collaborate with diverse teams.
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