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Health Insurance Claims EDA & Predictive Analysis
Built an end-to-end healthcare data analytics project focused on insurance claim patterns, patient risk factors, and cost prediction using Python and machine learning techniques.
This project involved data cleaning, exploratory data analysis (EDA), visualization, statistical insights, and predictive modeling to understand how factors like age, BMI, smoking habits, and medical conditions impact insurance charges.
What I worked on:
• Data preprocessing and cleaning
• Exploratory Data Analysis (EDA)
• Correlation and trend analysis
• Feature engineering
• Predictive ML models for insurance cost estimation
• Visual dashboards and statistical insights using matplotlib/seaborn
Tools & Technologies:
Python • Pandas • NumPy • Matplotlib • Seaborn • Scikit-learn • Jupyter Notebook
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
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Built an interactive sales performance dashboard to transform business data into actionable insights. Used reporting and KPI tracking concepts to monitor trends, validate data quality, and support data-driven decision making through clear visualizations and business-focused analytics.
I used to spend hours cleaning messy Excel files manually.
Now? I use AI tools to cut that time in half — and deliver better results to my clients.
Here's how AI has changed my freelance data workflow:
🔹 Faster data cleaning
Instead of manually hunting for duplicates and formatting errors, I use AI to flag inconsistencies instantly. What used to take 2 hours now takes 30 minutes.
🔹 Smarter dashboard structure
Before building any dashboard, I use AI to help me think through what metrics actually matter for that specific business — not just what looks good.
🔹 Better client communication
I use AI to help me write clearer project summaries and delivery notes — so clients understand exactly what they're getting and why it matters.
But here's what AI can't replace:
✔ Understanding what a CA firm actually needs vs what a D2C brand needs
✔ Knowing when a number looks wrong before the formula catches it
✔ The judgment that comes from actually working with real business data
AI is a tool. The thinking is still yours.
If you're a small business owner or CA firm drowning in Excel data — I can help you turn it into something you can actually use.
DM me or check my portfolio 👇
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Geethasree Naguboina
Data & Research Support Specialist | Excel Reports & Dashboards | AI Data Operations | Remote · Hyderabad, Telangana, India Skilled in data cleaning, validation, reporting, and structured workflows for teams and AI platforms. Email Me LinkedIn Profile
Developed a machine learning-based Heart Disease Prediction System with an interactive Streamlit interface for real-time prediction and analysis. The project involved data cleaning, exploratory data analysis, feature engineering, model training, and evaluation using Python and machine learning libraries.
The goal was to create a simple and user-friendly system that could help analyze patient health indicators and predict possible heart disease risk. Alongside the predictive model, the project also focused heavily on data visualization and interpretability.
Key tasks included:
• Data preprocessing and cleaning
• Exploratory Data Analysis (EDA)
• Correlation analysis and visualization
• Machine learning model building and evaluation
• Interactive Streamlit web app development
• Report writing and presentation preparation
Tools & Technologies:
Python, pandas, matplotlib, scikit-learn, Streamlit
This project was collaboratively developed with my teammate Gaurina as part of a university machine learning project.
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