Alwin

Aspiring Data Analyst and Machine Learning Enthusiast pursuing B.Tech in Data Science with strong skills in Python, SQL, and data analysis. Experienced in predictive modeling, feature engineering, and exploratory data analysis to extract data-driven insights. Hands-on experience working with real-world datasets to build, optimize, and evaluate machine learning models. Proficient in Pandas, NumPy, Scikit-learn, and Matplotlib for data processing, visualization, and performance analysis.

Machine Learning Intern at Zephyr Technologies Inc (2025-04 – 2025-05)

Developed and optimized machine learning models for healthcare predictions

• Developed a supervised machine learning model for heart disease prediction achieving approximately 85% accuracy on structured healthcare data.
• Processed and analyzed 500+ patient records including lifestyle habits and clinical features to build reliable prediction models.
• Performed feature engineering and exploratory data analysis to identify key risk factors influencing heart disease outcomes.
• Implemented and compared 3 classification algorithms (Logistic Regression, Decision Tree, Random Forest) to optimize model performance.
• Improved model accuracy by approximately 5–10% through iterative testing and tuning of model parameters.
• Evaluated model performance using accuracy, precision, recall, and F1-score to select the best-performing model.

B.Tech in Computer Science and Engineering (Data Science) – Christ University (2023-06 – 2027-05)