Computer Science graduate (B.Sc., Excellent with Honors, GPA 3.83/4.0) with 3+ years of experience applying machine learning and deep learning to biological, biomedical, and clinical data. Comfortable across the full ML lifecycle — data processing, feature engineering, model training, evaluation, and deployment — in Python, R. Hands-on with multi-omics and NGS data (genomics, transcriptomics, WES/WGS) alongside medical imaging, with 20+ delivered projects (94% Job Success Score) and a track record of interdisciplinary research collaboration. Strong communicator skilled at translating complex analyses into clear, actionable results for technical and non-technical stakeholders.