HR Analytics: engagement & compensation

Problem

HR teams sit on rich data about pay, engagement, and retention, but the patterns that matter — especially around fairness — are easy to miss. This project analyses HR data to surface those patterns and make them reviewable.

Approach

The work is exploratory data analysis paired with hypothesis testing: cleaning and summarising the data, then testing where differences in pay and engagement are large enough to warrant attention.

Data & inputs

• Engagement scores
• Salary and compensation records
• Retention and departmental performance signals

Key insights

• Identified a 15% salary disparity among junior roles
• Engagement was highest in departments with recognition programs
• Retention improved where compensation review was more transparent

Why it matters

Pay gaps and engagement gaps are hard to act on until they're made visible. Framing them as clear, evidence-backed findings gives an organisation something concrete to review.

Tools & technologies

Code & links

• GitHub repository — statistical summaries, charts, and hypothesis testing.