I’m Atharva
An Aspiring Data Scientist & Analyst, exploring all things data in Toronto.

This project builds a machine learning model to predict car insurance premiums using customer demographics, vehicle characteristics, and claim history. The goal is to help insurance companies price policies more accurately, manage risk effectively, and streamline the underwriting process, turning raw data into actionable insights for business decisions.

• Python
• Machine Learning
• Regression, Data Preprocessing
• Feature Engineering

Worked in a team to build an interactive dashboard mapping London’s crime risk. I focused on integrating multi-source data and developing the R Shiny dashboard for hotspots and risk scores.

• R
• RShiny
• leaflet, ggplot2, plotly
• Dashboards

LexiAI is an AI-powered QA assistant that helps users query dense legal documents and get clear, context-aware answers instantly. Built with NLP and LLMs, it goes beyond keyword search to summarize, interpret, and retrieve information—making legal knowledge more accessible and practical.

• Python
• NLP
• Large Language Models (LLMs)
• Text Summarization

Using the Ames Housing Dataset, I built a Linear Regression model to predict sale prices while minimizing RMSE. The project involved data cleaning, handling outliers, and encoding categorical features, showing how careful preprocessing and feature engineering can significantly improve model performance.

• Python
• Linear Regression
• Feature Engineering
• Data Preprocessing

Analyzing historical wildfire data in British Columbia, I explored spatial and temporal trends, identified key risk factors, and visualized high-risk zones. The project demonstrates how data-driven insights can inform wildfire management and mitigation efforts.

• R
• Data Analysis
• GIS / Spatial Analysis
• Data Visualization

As part of a team, we built a model to predict a recipe’s cuisine from its ingredients. My contributions included text preprocessing, feature engineering, and classification modeling. The project highlights how we transformed raw ingredient lists into accurate cuisine predictions, combining culinary intuition with data science.

• Python
• NLP
• Classification Modeling
• Machine Learning