BCG Data Science Job Simulation

This repository contains my completed work for the BCG Data Science Virtual Experience Program on Forage. The simulation provided hands-on experience in real-world data science tasks similar to those performed by BCG consultants.

🚀 Project Overview Through this job simulation, I applied data science techniques to analyze business problems, generate insights, and provide data-driven recommendations.

🔍 Key Learning Outcomes

1. Improved ability to clean and preprocess raw business data for meaningful analysis.
   
2. Strengthened understanding of statistical analysis and machine learning techniques.
   
3. Enhanced skills in using Python for data science tasks, including Pandas, NumPy, and Scikit-learn.
   
4. Gained hands-on experience in visualizing data and presenting insights using Matplotlib and Seaborn.
   
5. Developed problem-solving skills by applying data-driven methodologies to real-world consulting scenarios.
   

✅ Tasks Completed:

✅ Task 1:

• Use Python to analyze client data
  
• Create data visualizations to help you interpret key trends
  

✅ Task 2:

• Use Python to build a new feature for your analysis
  

✅ Task 3:

• Build a predictive model for churn using a random forest technique
  

✅ Task 4:

• Write an executive summary with your findings

📊 Technologies Used:

1. Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)
2. Jupyter Notebook

📌 Project Summary The project involved analyzing business data to uncover trends, make predictions, and support strategic decision-making using machine learning and data visualization techniques. The key focus areas included data preprocessing, exploratory data analysis, model building, and business insights.

👤 Author

Siddharth Gada
📧 Email: gadasiddharth@gmail.com
🔗 LinkedIn: https://www.linkedin.com/in/siddharthgada/