Data Annotator
Performed thorough data annotation across multiple machine learning projects to produce reliable datasets for model training and performance improvements. Built and applied efficient annotation guidelines to reduce average turnaround time while maintaining labeling quality and consistency. Partnered with data scientists to resolve labeling inconsistencies, improving dataset reliability and accuracy for critical AI use cases. • Conducted annotation work to ensure high-quality dataset outputs • Developed guidelines that reduced turnaround time by 30% • Collaborated with data scientists to correct inconsistencies (25% reliability improvement) • Implemented peer-review to decrease annotation errors by 15% and trained new annotators to boost productivity by 20%