Data Annotator
Contributed to a large-scale data labeling initiative to improve machine learning model accuracy for a natural language processing application. Annotated and classified 2,000+ text samples per week according to detailed guidelines, including sentiment analysis, intent recognition, and entity tagging. Maintained a consistency score above 95% across quality audits. Collaborated with the QA team to resolve edge cases and refine labeling criteria. Documented ambiguous examples and proposed guideline updates to improve team-wide alignment.