Computational Biology Data Annotation & Validation Specialist
Assisted in a computational biology-based AI training program, where complex scientific problems were developed, annotated, and validated. These problems were used for training, where complex scientific problems were developed, annotated, and validated. Annotated biological datasets and computational problems, ensuring accuracy, consistency, and adherence to scientific standards. Solutions were validated using Python-based scientific tools, such as NumPy, SciPy, and Biopython, for accuracy and precision in all deliverables. Ensured quality assurance by utilizing cross-verification, error checking, and detailed documentation of all methodologies. Assisted in enhancing the quality of datasets for machine learning-based applications, where high-quality annotated datasets were ensured, along with accurate outputs.