AI Data Labeling & Annotation Specialist – Healthcare & Administrative Data
Worked on data labeling and annotation projects focused on healthcare and administrative datasets. Responsibilities included annotating clinical text, categorizing patient-related information, and structuring unorganized data for machine learning model training. Performed tasks such as: Text classification of healthcare records and administrative documents Named Entity Recognition (NER) for patient data, diagnoses, and treatment-related terms Data categorization and tagging to improve AI model accuracy Reviewing and validating labeled datasets to ensure consistency and quality Handled medium to large datasets while maintaining high accuracy and adherence to annotation guidelines. Followed strict data privacy and confidentiality standards, especially when working with sensitive healthcare information. Quality assurance measures included double-checking annotations, peer reviews, and compliance with project-specific labeling instructions to ensure high-quality outputs suitable for AI training.