Through my freelance and personal projects, I develop and deploy machine-learning solutions using Python and tools including Scikit-learn, CatBoost, LightGBM, and XGBoost.
For a Trypanosoma cruzi inhibitor project, I developed a computational drug-discovery pipeline combining QSAR machine learning with molecular docking, MM-GBSA, and SwissADME analysis.
I also built projects applying machine learning to biomedical and workforce data, including Parkinson’s disease prediction from voice measurements and employee attrition prediction. The Parkinson’s project exposes its predictions through a RESTful API.
With a pharmacy degree from Nnamdi Azikiwe University, Awka, Nigeria, and supervised pharmacy internship and NYSC experience, I bring pharmaceutical training to my work in data science and computational drug discovery. I’ve supplemented that training with certifications in data science, machine learning, Python, SQL, and AI.
