Data Scientist and Applied Statistician with expertise in predictive analytics, machine learning, and statistical modeling. Experienced in delivering high-impact solutions across healthcare, education, and public sectors, including disease prediction models (80.5% accuracy) and student performance systems (98.86% R²). Proficient in Python, R, and advanced techniques such as XGBoost, Random Forest, and SVM, with hands-on experience designing end-to-end ETL pipelines. Skilled at leading research initiatives and translating complex data into actionable insights to drive informed decision-making.