Interactive Website, Data Analysis, AI/Machine Learning Model

About the project

• Engineered and deployed a 5-page interactive website using HTML5, JavaScript, and Bootstrap, configured hosting infrastructure through GoDaddy and Cloudflare. • Researched and compiled data on 100+ U.S. medical practitioners to build a structured prospect dataset. • Cleansed and validated clinical data using MS Excel and Google Sheets, improving data accuracy and usability to 95%. • Monitored and automated website performance, DNS, and SSL/TLS infrastructure using Cloudflare and cPanel,saving 10+ hours per week. Analyzed 500K+ financial transactions to build an AI-powered tax fraud detection and risk monitoring system. • Led a team and engineered 27 data features and optimized machine learning classification models to enhance anomalous behavior detection. • Achieved 88% accuracy in identifying high-risk taxpayers through advanced predictive modeling. • Developed a scalable analytics pipeline using PySpark for distributed data processing and an interactive Streamlit dashboard with 7 analytical views with KPIs, Tables and Graphs for real-time compliance monitoring. Built an end-to-end ETL data analytics pipeline with 500K+ transaction records for customer purchasing insights. • Preprocessed the dataset, performed an 80/20 train-test split, and conducted EDA and feature engineering. • Designed customer segmentation ML models using RFM analysis to classify users into 3 behavioral groups. • Improved decision-making and strategic planning by delivering classification Machine Learning models with a 92% prediction accuracy

Skills required