About

In this project, I used Zerve’s AI-native notebook and adaptive agent to analyze employee performance data and understand what drives long-term success and salary growth. I defined success as a combination of productivity, skill level, leadership, and consistent performance. Using Zerve, I engineered meaningful features, explored behavioral and performance patterns, and trained a machine learning model to predict salary outcomes. The analysis shows that skill development, leadership ability, and project impact are stronger predictors of growth than experience alone. This project demonstrates how AI-powered data workspaces like Zerve can turn raw performance data into actionable insights for fair, data-driven HR and talent decisions.