AI Data Quality Specialist
6 days ago
We are seeking a detail-oriented and analytical professional to ensure the accuracy and reliability of AI models. This role involves performing quality audits, statistical reporting, and root cause analysis to identify areas for improvement.
The ideal candidate will have 1+ years of experience in data analysis, particularly in AI/ML contexts, and be familiar with basic concepts of AI/ML pipelines and data. Strong analytical and problem-solving skills are essential, along with excellent written and verbal communication skills.
Perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.
Use metrics such as F1 score and inter-annotator agreement to evaluate data quality.
Analyze annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.
Resolve and analyze edge-case annotations to ensure quality and identify improvement areas.
Proficiently use annotation and quality control tools to perform reviews and track quality metrics.
Develop expertise in project guidelines and provide feedback for clarifications or improvements.
Identify automation opportunities and contribute to documentation of quality standards and procedures.
This is a remote position that offers flexibility and opportunities for growth. The successful candidate will make a significant impact by ensuring data integrity through audits, pinpointing and resolving annotation issues, optimizing annotation processes, and collaborating with stakeholders.
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