coded72

Annotated 50,000+ data points across text, image, and video datasets with 98% accuracy, supporting computer vision and NLP model development for autonomous vehicles, sentiment analysis, and medical imaging applications. Performed quality assurance on 10,000+ weekly annotations and collaborated with ML engineers to refine annotation guidelines, reducing ambiguity by 40% and improving model training efficiency Led annotation projects including autonomous vehicle object detection (20,000+ street scenes, 99.2% inter-annotator agreement), e-commerce sentiment analysis (15,000+ reviews, 89% F1-score), and medical image segmentation (5,000+ scans, 92% accuracy). Trained and mentored 5 junior annotators on best practices and developed custom workflows that reduced task completion time by 30% while maintaining quality standards.