Pharmaceutical HR Analytics

This comprehensive HR analytics project analyzes workforce data from a major pharmaceutical company to derive actionable insights for human resource management and strategic decision-making. The analysis covers various aspects of employee data including performance metrics, retention patterns, compensation analysis, and workforce demographics.

The project employs advanced statistical techniques and exploratory data analysis (EDA) to uncover hidden patterns in HR data. Using R's powerful statistical computing capabilities, the analysis includes correlation analysis, regression modeling, and predictive analytics to understand factors affecting employee satisfaction, performance, and retention.

The study includes comprehensive data visualization using ggplot2 and other R visualization libraries to create compelling dashboards and reports. Interactive visualizations help stakeholders understand complex HR metrics and trends, enabling data-driven decision-making in human resource management.

This project demonstrates the practical application of statistical analysis and data science in human resources, showcasing how analytics can transform traditional HR practices into strategic, evidence-based management approaches.