Vansh Tejiya

I’m a B.Tech Computer Science undergraduate focused on turning complex data into clear, actionable insights. I work confidently with SQL and Python (Pandas, NumPy) and build analytics workflows around machine learning and reporting.

In my projects, I built a fraud detection model in Python that achieved ~94% accuracy by preprocessing with Pandas, engineering features, and training/evaluating classification models using scikit-learn. I also created an end-to-end customer market segmentation pipeline for 2,240 records, clustering customers into 4 behavioral groups with K-Means, and deployed an interactive Streamlit dashboard that reduced analyst reporting time by 30%.

I complement analytics with strong fundamentals from software work, including a Java + MySQL payroll management system using core OOP principles and JDBC for persistent storage and CRUD operations. I enjoy data simulations too—using tools like Tableau and Excel to turn messy inputs into business conclusions.