Vinay Hulsurkar

Education

Honours in Data Science

Nov 2022 – June 2026

Dr. D. Y. Patil College Of Engineering And Innovation, Pune

CGPA: 8.66 / 10.00 ( till 7th Semester )

Jan 2025 – Feb 2025

Built a customer segmentation model using K-Means (Scikit-learn) to group customers and support targeted marketing decisions.
Developed a house price prediction model using Linear Regression, improving prediction accuracy and reducing RMSE compared to the baseline.
Analyzed 100K+ superstore sales transactions and student performance data to uncover trends and identify key factors influencing outcomes.

Python, Pandas, Scikit-learn, Streamlit, Plotly

Built and deployed a personal finance analytics web app that processes raw bank transaction data to generate insights on spending patterns, savings behaviour, and financial trends.
Implemented transaction categorization, anomaly detection (Isolation Forest), and expense forecasting models to identify unusual transactions and estimate future spending.
Developed interactive dashboards and a Financial Health Score (0–100) using Streamlit and Plotly to visualize financial metrics and support budget planning.

Python, Pandas, Matplotlib, Seaborn

Built a stock trend analysis tool using 5+ years of historical RIL data (~50K data points) to study price movements and identify investment patterns.
Developed time-series forecasting models and moving-average based analysis to detect short-term trends and potential trading signals.
Created interactive visualizations with Matplotlib and Seaborn to highlight volatility zones, support/resistance levels, and seasonal patterns for easier analysis.

Python, Flask, yt-dlp, HTML, CSS

Developed a full-stack web application to download YouTube videos with real-time preview and format selection, handling both metadata extraction and media processing using yt-dlp.
Engineered backend APIs with Flask to manage video parsing, preview generation, and download workflows, ensuring smooth interaction between frontend and server
Designed a minimal, responsive UI with custom animations and loading states, enhancing user experience and making the tool intuitive and visually clean.
Deployed the application on Render, enabling public access and demonstrating end-to-end development from backend logic to production deployment.

Python, Scikit-learn, Streamlit, Plotly

Built a property valuation and loan risk analysis tool covering 10 Indian cities using a realistic synthetic dataset (~5K records).
Trained a Random Forest model (R² ≈ 0.97) to predict housing prices and added CAGR-based forecasting for long-term investment insights.
Integrated credit risk logic (DTI & LTI) to estimate loan eligibility, interest rates, and EMI affordability, supported by interactive visualizations.

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Languages used: Python, JavaScript, SQL

175+ Problems Solved
Contest Rating: 1712
Top 12% of Leetcode users.

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Programming: Python, JavaScript, TypeScript, SQL
Web Development: React.js, Node.js, HTML, CSS, FastAPI, Flask
Data Science & Machine Learning: NumPy, Pandas, Scikit-learn, TensorFlow, Keras, PyTorch
Statistical Analysis, Predictive Modeling, Regression, Time-Series Forecasting, Natural Language Processing (NLP)
Databases & Visualization: MySQL, MongoDB, SQLite
Microsoft Excel, Tableau, Power BI, Matplotlib, Seaborn, Streamlit
Tools & CS Fundamentals: Git, GitHub, VS Code, Jupyter, Google Colab
DSA, OOP, DBMS, OS, Computer Networks
AI Tools: Gemini, ChatGPT, Claude, Perplexity, Grok, Emergent