https://github.com/edaaydinea/datascienceforbusiness
This repository includes 6 real-world case studies in data science for business.
https://github.com/edaaydinea/datascienceforbusiness
Last synced: 7 months ago
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This repository includes 6 real-world case studies in data science for business.
- Host: GitHub
- URL: https://github.com/edaaydinea/datascienceforbusiness
- Owner: edaaydinea
- License: apache-2.0
- Created: 2025-01-05T17:06:35.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-01-09T17:33:30.000Z (9 months ago)
- Last Synced: 2025-01-09T18:37:43.174Z (9 months ago)
- Language: Jupyter Notebook
- Size: 1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DataScienceForBusiness
This repository includes six real-world case studies in data science applied to business scenarios.
## Case Study 1: Employee Attrition Prediction
### **Overview**
Employee attrition is a significant challenge for organizations, leading to high costs and reduced productivity. This case study focuses on using machine learning to predict employee attrition and empower HR teams to make proactive, data-driven decisions.
### **Problem Statement**
- **High Costs of Hiring**: Recruiting a new employee costs 15%-20% of their salary, with an average of $7,645 for small companies.
- **Retention Challenges**: Understanding factors like job satisfaction and work-life balance is critical.
- **Need for Prediction**: An ML-based model is required to identify employees likely to quit.
### **Business Impact**
1. **Cost Savings**: Minimize hiring costs and revenue losses.
2. **Increased Productivity**: Retain top talent and reduce turnover.
3. **Strategic Planning**: Optimize workforce management using model insights.
### **Dataset Features**
- Includes variables such as job involvement, education, job satisfaction, performance ratings, and work-life balance.
### **Approach**
- Models like logistic regression, random forests, and neural networks will be used to predict attrition and support HR strategies.
Explore this [case study](https://github.com/edaaydinea/DataScienceForBusiness/blob/main/1.%20Human%20Resources%20Data/Human_Resources_Department.ipynb) to see how data science can transform HR challenges into actionable solutions!