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Data Science Trainee
AlmaBetter
Aug 2023 - Present • 2 yrs 9 mos
Developed an ML model to predict the likelihood of heart disease in individuals using medical data (918 patients, 12 health features). using Logistic Regression, Random Forest, and XGBoost, applying SMOTE to balance classes and prioritizing recall to reduce false negatives. Achieved 90% Precision, 90% Recall, 90% F1-score, 90% Accuracy, and 90% ROC AUC, outperforming baseline models and enabling early diagnosis for high-risk patients, improving outcomes and supporting preventive healthcare. Recognized in the Top 10 of 100 in cohort for project quality and analytical rigor.