An explanation-first HR analytics system that reconstructs why employee exit becomes rational. Instead of predicting attrition, it generates human-readable exit narratives by decomposing pressure and retention forces, adding peer context and counterfactual interventions to reveal how stability erodes over time.

Developed an interactive HR attrition analysis dashboard using Power BI to gain insights into employee turnover and identify key attrition reasons within the organization. By analyzing attrition trends and visualizing relevant metrics, the dashboard helps HR professionals understand the underlying causes of attrition.

Predicting employee attrition entails gathering historical data on employees, identifying key features, training machine learning models, and deploying them for real-time predictions to aid in retention strategies and organizational stability. Regular monitoring and updates ensure ongoing effectiveness.

A Power BI-driven HR analytics project that visualizes employee attrition trends, performance metrics, and demographic insights. Includes data cleaning, modeling, and dashboard development using Power Query and DAX. Offers actionable recommendations to support HR strategies for employee retention, diversity, and satisfaction across departments.

This repository contains a Power Bi dashboard of IBM HR Analytics to answer some questions about the employee attrition and performance data. This repository can be used as a starting point for anyone who wants to learn how to use Power Bi to analyze data.

This project uses HR analytics to identify key factors contributing to high employee attrition rates, helping organizations understand and mitigate turnover issues.

PowerBI visualization Portfolio

End-to-End Data Analyst project on employee attrition using Python, MySQL, and Logistic Regression. Covers full EDA, SQL analytics, and predictive modeling for HR decision-making, risk segmentation, business KPIs, and actionable retention strategy.

Sales Analysis/HR Analytics

In this project, I visualized and analyzed a company's Human Resource dataset using the Tableau BI tool in a bid to draw insights that are set to gauge the company's attrition rate.

EDA on HR dataset to understand employee attrition patterns.

The goal of this project is to analyze employee retention data to uncover insights that can help improve retention strategies. By identifying key factors that influence employee attrition, we aim to provide actionable recommendations for enhancing employee satisfaction and retention rates.

A Dashboard made in Excel showing the trend of how employees left the organization.

Predictive analysis using Logistic Regression to identify key drivers of employee attrition. This project focuses on optimizing model sensitivity (83.37%) to help HR departments proactively engage at-risk talent and improve retention strategies

"Exploratory Data Analysis (EDA) on employee dataset using Python and pandas to uncover HR trends, attrition patterns, and workforce insights."

The 3 projects files to MeriSKILL is presented here

Power BI attrition data dashboard

This case study looked at the attrition rate and performance of employees. This was done by performing a descriptive and diagnostic analytics with SQL

Employee attrition prediction system. | Framework: Flask (Python), Bootstrap.