

Data Science undergraduate skilled in Python, SQL, Excel, and Tableau with hands-on projects in healthcare analytics, machine learning, and business dashboards. Strong foundation in data cleaning, visualization, and deriving insights to support decision-making.
Data analysis tools
- Database Management: SQL (queries, joins, aggregations)
- Machine Learning: Scikit-learn (classification, prediction models)
Programming in Python
Excel formulas
Data cleaning
Tableau software
SQL and databases
Hospital Patient Data Analysis
Analyzed 5,000+ patient records using Python & SQL to identify disease patterns and optimize treatment outcomes.
Visualized trends with Matplotlib & Seaborn.
IPL Match Winner Prediction
Built Random Forest model achieving ~80% accuracy in predicting match winners.
Conducted EDA and feature engineering on historical match data.
E‑Commerce Sales Dashboard (Tableau)
Created interactive dashboard reducing reporting time by 40%.
Highlighted Pareto distribution (top 20% customers driving 80% revenue).