Welcome to Salifort Motors, a visionary French-based alternative energy vehicle manufacturer. With a global workforce exceeding 100,000 employees, we are at the forefront of research, design, construction, validation, and distribution of cutting-edge electric, solar, algae, and hydrogen-based vehicles. Salifort Motors is committed to revolutionizing the automotive industry through innovation and sustainability.
"At Salifort Motors, we are dedicated to providing a sustainable and efficient future through the development and production of alternative energy vehicles. Our commitment to excellence, innovation, and environmental responsibility drives us to be a global leader at the crossroads of alternative energy and automobiles."
As a valued data specialist at Salifort Motors, you are entrusted with a critical task: analyzing the results of a recent employee survey. The senior leadership team recognizes the importance of employee retention and has specifically tasked you with leveraging your expertise to devise strategies for increasing it.
The primary objectives of your analysis are as follows:
Identify key factors influencing employee retention at Salifort Motors.
Design a predictive model that can forecast whether an employee is likely to leave the company.
Consider various data points, including department, number of projects, average monthly hours, and any other relevant factors that may contribute to employee retention.
For this deliverable, you are asked to choose a method to approach this data challenge based on your prior coursework. Select either a regression model or a tree-based machine learning model to predict whether an employee will leave the company. Both approaches are shown in the project exemplar, but only one is needed to complete your project. The capstone project will provide you with valuable experience and data analysis examples that you can share with potential employers.
We appreciate the collaboration of the HR department at Salifort Motors for providing the necessary data for this project. Special thanks to the Python community for their contributions to data analysis and visualization tools. May this project empower HR professionals at Salifort Motors in making informed decisions for organizational success.