Remotask — Data Analysis & Data Labeler (Data labeling and QA for ML/AI projects)
Collected raw datasets from surveys, system logs, and online platforms to support downstream analysis and labeling work. Cleaned and standardized datasets by removing duplicates, correcting errors, and ensuring consistent formatting. Labeled and categorized data (such as text/product information) according to project guidelines for machine learning and AI training. • Followed annotation instructions and project-specific schemas. • Performed data cleaning steps to improve dataset quality. • Completed quality checks to ensure label consistency. • Validated labeled outputs to meet accuracy standards.