Data labeling and annotation (quality review) focus—student/project experience (no formal employer listed)
Experience focused on preparing and reviewing labeled data for quality and accuracy in AI/data annotation workflows. Conducts data quality checks by verifying consistency, completeness, and adherence to provided instructions. Applies attention to detail to reduce errors and improve dataset reliability. • Reviews annotation outputs for quality and correctness • Follows labeling guidelines and task instructions closely • Uses systematic checks to ensure data consistency • Supports dataset readiness for downstream AI training