Veronicah Wairimu Kabi

I’m a motivated data science student with a strong foundation in Python, SQL, and data analytics. I’m passionate about using data-driven insights to improve decision-making, especially in healthcare analytics and AI-powered solutions.

Through an attachment experience at a hospital, I analyzed sick leave patterns by tracking lost and working hours, and supported operations by entering candidate information and recording doctors’ payrolls monthly. I like combining careful analysis with practical, real-world context—so insights translate into better actions.

I build end-to-end ML applications, including deep learning and computer vision projects. For my Automated Leukemia Detection System, I used transfer learning with a pretrained ResNet50 model and achieved 76% validation accuracy with 92% recall, along with an interactive Streamlit app for prediction, PDF reporting, and prediction history. I also integrated APIs for payment processing (Safaricom M-Pesa Daraja) and patient identity verification (Gava Connect).

My coursework and projects keep strengthening my skills in model evaluation, visualization, and experimentation. I’m currently seeking an attachment opportunity where I can apply my analytical and problem-solving abilities to real-world data challenges and keep improving my AI/ML craft.