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Salifort Motors Capstone Project

Google Advanced Data Analytics Capstone Project

Provide data-driven suggestions for HR

Currently, there is a high rate of turnover among Salifort employees. (Note: In this context, turnover data includes both employees who choose to quit their job and employees who are let go). Salifort’s senior leadership team is concerned about how many employees are leaving the company. Salifort strives to create a corporate culture that supports employee success and professional development. Further, the high turnover rate is costly in the financial sense. Salifort makes a big investment in recruiting, training, and upskilling its employees. If Salifort could predict whether an employee will leave the company, and discover the reasons behind their departure, they could better understand the problem and develop a solution. As a first step, the leadership team asks Human Resources to survey a sample of employees to learn more about what might be driving turnover. Next, the leadership team asks you to analyze the survey data and come up with ideas for how to increase employee retention. To help with this, they suggest you design a model that predicts whether an employee will leave the company based on their job title, department, number of projects, average monthly hours, and any other relevant data points. A good model will help the company increase retention and job satisfaction for current employees, and save money and time training new employees.

What’s likely to make the employee leave the company?

Deliverables

Analyze the key factors driving employee turnover, build an effective model, and share recommendations for next steps with the leadership team.

  • Model evaluation
  • Data visualizations
  • Ethical considerations
  • Resources
  • One-page summary of this project

HR dataset

In this dataset, there are 14,999 rows, 10 columns, and these variables:

Variable Description
satisfaction_level Employee-reported job satisfaction level [0–1]
last_evaluation Score of employee's last performance review [0–1]
number_project Number of projects employee contributes to
average_monthly_hours Average number of hours employee worked per month
time_spend_company How long the employee has been with the company (years)
Work_accident Whether or not the employee experienced an accident while at work
left Whether or not the employee left the company
promotion_last_5years Whether or not the employee was promoted in the last 5 years
Department The employee's department
salary The employee's salary (U.S. dollars)

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