This repository contains the findings and insights from a comprehensive analysis on employee attrition and job satisfaction within the organization. The project aimed to identify key factors influencing turnover and provide actionable strategies to mitigate attrition rates. Through statistical analysis and data-driven approaches, the project sought to uncover patterns, trends, and potential early indicators of attrition, enabling proactive interventions to improve employee retention and satisfaction. The analysis delved into various dimensions such as departmental dynamics, job roles, and demographic factors to provide a holistic understanding of attrition drivers and develop targeted strategies to address them. Ultimately, the project aimed to foster a positive work environment conducive to employee engagement, growth, and long-term retention.
- Identified variances in attrition rates across demographic and operational segments.
- Key factors contributing to attrition: lack of career development, job dissatisfaction, and inadequate recognition or compensation.
- Conducted statistical analyses pinpointing predictors such as job satisfaction levels and performance ratings, highlighting early signs for intervention.
- Conducted sentiment analysis on social media data to extract actionable insights, informing decision-making and effectively monitoring public sentiment trends.
- Utilized Python data science skills and libraries in team projects, applying theoretical knowledge to real-world scenarios, and enhancing problem-solving and collaboration abilities.