A data annotator reviews raw datasets and assigns labels according to specific project guidelines. Their work may include identifying objects in images, categorizing text, transcribing audio, tagging video content, or highlighting relevant information in documents. Accuracy and consistency are important because the labeled dataset may be used to train machine learning models. Annotators usually follow detailed instructions and may work with quality-control teams to identify mistakes. Depending on the project, they can use specialized annotation software that provides tools for marking, categorizing, reviewing, and organizing different types of data.
