Portobello Tech is an app innovator that has devised an intelligent way of predicting employee turnover within the company. It periodically evaluates employees' work details including the number of projects they worked upon, average monthly working hours, time spent in the company, promotions in the last 5 years, and salary level.
Data from prior evaluations show the employee’s satisfaction at the workplace. The data could be used to identify patterns in work style and their interest to continue to work in the company.
The HR Department owns the data and uses it to predict employee turnover. Employee turnover refers to the total number of workers who leave a company over a certain time period.
Details of the dataset:
satisfaction_level; satisfaction level at the job of an employee
last_evaluation: Rating between 0 to 1, received by an employee at his last evaluation
number_project: Number of projects, an employee involved in
average_montly_hours: Average number of hours in a month, spent by an employee at office
time_spend_company: Number of years spent in the company
Work_accident: 0 - no accident during employee stay, 1 - accident during employee stay
left: 0 indicates employee stays in the company,1 indicates - employee left the company
promotion_last_5years: Number of promotions in his stay
Department: Department, an employee belongs to
salary: Salary in USD