Discover my analytical journey
Healthcare Insurance Risk Analysis
This project analyzes insurance claims based on a person's lifestyle and health conditions. After cleaning the data and performing EDA, I examined how factors like smoking, exercise, and medical conditions impact claim amounts.
Using Random Forest Regression, I built a model to predict a person’s expected vs. actual claim, helping assess their risk level for insurers. Based on this, companies can offer customized insurance plans. Key insights are visualized through an interactive Power BI dashboard for better decision-making.
Integrated Business Metrics Analyzer
In this project, I brought together multiple CSV files into a single, powerful dataset using SQL and visualized the data relationships with an ER diagram in Lucid chart. This streamlined our database structure, making financial reporting clearer and more efficient.
Next, I dove into the data with Python, cleaning and analyzing it to uncover valuable insights. I created interactive visualizations that helped stakeholders make informed decisions and predict future financial trends with confidence.
S&P 500 Index Market Anomaly Tracker
Developed a Python-based anomaly detection system for the S&P 500 index (2022–2024), leveraging statistical methods like IQR and Z-scores to flag significant deviations in price and trading patterns. Identified key risk factors and unusual market behaviors, enabling proactive management of portfolio exposure during volatile conditions.
Conducted granular analysis of financial anomalies to uncover hidden trends, supporting strategic decision-making in volatility mitigation and asset allocation. Visualized findings through interactive dashboards to highlight actionable insights for optimizing investment strategies and balancing risk-reward tradeoffs.
Sales Analysis
In this project, I analyzed Amazon sales data to understand customer behavior, revenue trends, and product performance. After cleaning the data, I performed exploratory data analysis (EDA) to identify patterns like seasonal trends, best-selling products, and factors affecting sales fluctuations.
The goal was to uncover insights into what drives sales and how different factors impact revenue, helping businesses make better decisions based on data.
Create Your Own Website With Webador