Wangari Kamau

I am a Junior Data Scientist with practical experience in machine learning, data cleaning, exploratory data analysis, and interactive dashboarding. I have a BSc in Information Technology and hands-on training through an industry attache program.

During my Safra Data attache I gained experience using Jupyter Notebooks and core Python libraries such as NumPy, Pandas, Matplotlib, and Seaborn to manipulate, analyze, and visualize data. I worked on supervised learning models including Linear and Logistic Regression, KNN, Decision Trees, SVM, Random Forest, and XGBoost.

My projects include cleaning and visualizing healthcare datasets, building a diabetes prediction model with cross-validation and AUC scoring, analyzing Jumia operations and producing an operations dashboard, and completing the Titanic classification project. These experiences demonstrate my end-to-end ML workflow competence—from preprocessing and feature engineering to model evaluation and interpretation.

I am passionate about transforming raw data into actionable insights and contributing to mission-driven technology teams, bringing strong practical skills in data handling, KPI reporting, dashboard building, and model deployment readiness.