Fauziyya Abdullahi

I am a data science–focused Computer Science undergraduate with over two years of hands-on experience in machine learning, predictive modeling, and data-driven research. I combine strong foundations in Python with applied experience in model evaluation and explainability.

I have designed end-to-end ML solutions—covering data preprocessing, feature engineering, model training, and deployment—across projects including traffic forecasting, churn prediction, handwriting recognition, and recommendation systems. I apply tools such as Scikit-learn, TensorFlow/Keras, SHAP, and FastAPI to produce reproducible, production-ready outcomes.

As a co-founder and lead instructor of a student-led initiative, I have delivered bootcamps to over 200 students and translated technical results for diverse stakeholders. My work has been recognized with awards including a Best Paper award for predictive traffic models and a campus Hult Prize win.

I am committed to building scalable, explainable ML solutions and contributing to teams that value data-driven decision-making, continuous learning, and impact-driven projects.