📊 HR Analytics: Engagement & Compensation

🧠 Overview

This project analyzes HR data to uncover insights around employee engagement, salary disparities, departmental performance, and workforce retention. Using Python and data visualization tools, we provide evidence-backed recommendations for improving employee satisfaction and fairness.

📂 Project Report & Notebook

• 🔗 View GitHub Repository
• Includes statistical summaries, charts, and hypothesis testing

⚙️ Tools & Technologies

• Python, Pandas, Matplotlib, Seaborn
• Exploratory data analysis & hypothesis testing
• HR metrics: engagement score, salary fairness, retention trends

📊 Key Insights

• 📈 Identified 15% salary disparity among junior roles
• 💬 Engagement levels highest in departments with recognition programs
• 🚪 Retention improved with transparency in compensation review

📈 Visual Summaries

1. Salary Spread

Standard deviation and range across departments

2. Engagement Scores

Confidence interval by performance rating

3. Special Projects Load

Project count variation by job position