Data labelling
Accurately labeled and annotated 5,000+ images, text documents, and audio files to train machine learning models, achieving 98%+ accuracy rate consistently above project benchmarks. Performed data labeling tasks including bounding boxes, semantic segmentation, sentiment analysis, named entity recognition (NER), and intent classification. Maintained high quality standards under strict guidelines while meeting daily/weekly targets, resulting in consistent positive performance reviews and increased task allocation.