Raghavendra S

Data Science graduate skilled in Python, SQL, Machine Learning, and Data Visualization. Experienced in handling large datasets, feature engineering, and predictive modelling. Led multiple data-driven projects, applying statistical analysis and ML algorithms to extract actionable insights. Seeking an entry-level Data Scientist role to apply analytical and problem-solving skills in a dynamic team environment.

Project Title: Empowering Early Detection of Heart Attack Risks with Machine Learning
Role: Team Leader | Domain: Healthcare AI | Team Size: 6

Objective:

· Developed a machine learning model to predict heart attack risks using patient health records.

· Enabled early detection, reducing healthcare costs and improving patient outcomes.

Data & Preprocessing:

Dataset: 4,45,152 records, 40 features (34 categorical, 6 numerical).

Preprocessing: Handled missing values, feature engineering, encoding, and scaling.

Class Imbalance: Addressed using undersampling & class weights.

Model Development & Results:

• Evaluated Logistic Regression, Decision Tree, Random Forest, XGBoost, AdaBoost, Gradient Boosting, Naïve Bayes, KNN.
• Best Model: XGBoost → 83% Accuracy, 81% Recall, 0.905 AUC-ROC.
• Hyperparameter Tuning: Used GridSearchCV for optimization.

Business Impact:

• Supports hospitals in risk assessment and early intervention for high-risk patients.
• Future Scope: SHAP interpretability, wearable integration, ensemble learning.

Skills Used: Python (Scikit-learn, NumPy, Pandas), SQL, Excel, Tableau, Feature Engineering, Model Evaluation, Data Visualization.

· Telecom Customer Churn Analysis (Tableau)

· Conducted EDA to identify customer churn trends and demographics.

· Segmented customers using clustering techniques to detect high-risk groups.

· Built interactive dashboards for churn rate visualization and analysis.

· Skills Used: Tableau, Data Visualization, Customer Segmentation, Dashboarding.

·  IPL Match Bidding Analysis (SQL)

· Designed a relational database for IPL match bidding and performance tracking.

· Developed complex SQL queries to analyze match outcomes, team performance, and revenue.

· Optimized indexes and constraints for efficient query execution.

· Skills Used: SQL, Database Design, Query Optimization, Business Intelligence.

·  Airbnb Price Analysis (Excel)

· Cleaned and processed large Airbnb datasets, handling missing values and duplicates.

· Performed EDA to identify pricing trends based on room type, review scores, and demand.

· Created dynamic dashboards using pivot tables & charts for price trend visualization.

· Skills Used: Excel, Data Cleaning, Pivot Tables, Charts, Dashboards.

· Supply Chain Analysis (SQL)

· Executed SQL queries for supplier performance, revenue tracking, and cost savings.

· Analyzed customer trends and optimized supply chain workflows.

· Skills Used: SQL, Data Analysis, Query Optimization, Business Intelligence.

· Zomato Data Analysis (Python)

· Performed EDA on Zomato data to analyze restaurant ratings, pricing, and customer behavior.

· Provided insights into restaurant marketing strategies and pricing optimization.

· Skills Used: Python, Pandas, NumPy, Matplotlib, Seaborn.

· House Price Case Study (Excel)

· Analyzed 17,594 real estate records to identify pricing trends and key factors.

· Used pivot tables, charts, and macros to automate reporting.

· Skills Used: Excel, Data Cleaning, Dashboards, Automation.

• Data Analytics using Excel, Great Learning, 2025
• Introduction to AI, Great Learning, 2025
• Mathematics for Data Science, Udemy, 2025
• SQL (Basic & Intermediate), HackerRank, 2025
• Python (Basic & Intermediate), HackerRank, 2025

• English, Fluent
• Kannada, Native