Data Annotation
I have performed a range of data annotation tasks including text classification, sentiment labeling, content moderation, entity recognition, and AI response evaluation. My work involved labeling datasets for machine learning models, categorizing content based on predefined guidelines, reviewing AI-generated outputs for accuracy, and identifying inconsistencies or errors in labeled data. I also handled tasks such as tagging keywords, classifying user intent, and organizing structured datasets to support AI model training and evaluation. To ensure high-quality results, I strictly adhered to annotation guidelines, maintained consistency across datasets, and conducted regular self-quality checks before submission. I focused on accuracy, attention to detail, and meeting project-specific requirements such as inter-annotator agreement, clear documentation, and timely delivery. I also reviewed edge cases carefully, flagged ambiguous data, and followed quality control processes to ensure reliable and scalable training data for AI models.