Tayyaba N.

I’m a PhD-trained biomolecular scientist and AI Data Scientist with hands-on experience across dataset curation, large-scale data pipelines, and scientific research/writing. I bring a rare combination, solid Python-based data engineering skills paired with deep domain expertise in biology, biochemistry, and bioinformatics. Data Science & AI: On a recent engagement (AutoDebugger project), I curated and maintained a 100K+ entry multi-source dataset library across diverse datasets, built a four-factor data quality scoring framework used for training data selection, and engineered graph-based analysis pipelines on AWS EC2 across 375+ repositories and 51,000+ code samples. I also produced technical reports for leadership on model performance and dataset quality. Bioinformatics & Research: PhD in Biomolecular and Health Sciences, with laboratory and computational research spanning molecular docking (AutoDock Vina, PyMOL, Chimera), cell biology techniques (Western blot, PCR, microscopy), and scientific manuscript writing. I’ve authored research papers and conference presentations. What I offer: • Python-based EDA, data cleaning, and pipeline development (Pandas, NumPy) • Dataset quality assessment and curation for ML/AI training • Bioinformatics analysis and computational drug/protein design support • Scientific/technical writing, literature review, and manuscript editing • Clear, reliable communication and on-time delivery I care about accuracy and transparency. I only take on work that matches my real skill set, and I’m upfront about what I’m still building expertise in.