Employee Survival Prediction Data

Columns

• Age: The employee's age, ranging from 18 to 60.
• Attrition: A boolean field indicating whether the employee has left the organisation (16% True).
• BusinessTravel: Indicates the frequency of business travel, with 'Travel_Rarely' being the most common category (71%).
• Department: The department of employment, where Research & Development accounts for 65% of records.
• DistanceFromHome: The daily distance travelled by the employee to reach work, ranging from 1 to 29 miles.
• Gender: Gender of the employee, with 60% being Male.
• JobInvolvement: The rating (1 to 4) reflecting employee involvement in their job.
• JobLevel: The level (1 to 5) at which the employee is working.
• JobRole: The specific roles and responsibilities, with 'Sales Executive' being the most frequent.
• JobSatisfaction: The employee's satisfaction rating (1 to 4) with their job.
• MaritalStatus: Marital status of the employee, with 'Married' being the most reported status (46%).
• MonthlyIncome: The employees' monthly income, spanning from £1,009 to £20,000.
• NumCompaniesWorked: The total number of companies the employee has worked for, from 0 to 9.
• OverTime: A boolean indicating if the employee works Overtime (28% True).
• PercentSalaryHike: The percentage salary increase since their appointment, ranging from 11% to 25%.
• PerformanceRating: The performance rating of the employee, generally 3 or 4.
• StockOptionLevel: The level (0 to 3) of opted-for stock sharing.
• TotalWorkingYears: The total years worked by the employees, up to 40 years.
• TrainingTimesLastYear: Number of trainings undertaken by the employee, 0 to 6.
• YearsAtCompany: Years spent at the current organisation, up to 40 years.
• YearsSinceLastPromotion: Time elapsed in years since the last promotion, up to 15 years.
• YearsWithCurrManager: Years working under the current manager, up to 17 years.
• Higher_Education: The employee's higher education level.
• Date_of_Hire: Date the employee was hired in the current organisation.
• Date_of_termination: Date of termination (Note: 100% missing data in sample).
• Status_of_leaving: The stated reason for leaving the organisation.
• Mode_of_work: Indicates if the work mode is WFH (52%) or OFFICE (48%).
• Leaves: Total permitted leaves taken by the employee (0 to 5 days).
• Absenteeism: Total days the employee was absent (0 to 3 days).
• Work_accident: A boolean indicating if a work accident occurred (50% True).
• Source_of_Hire: The recruitment source (Recruiter 27%, Job Event 25%).
• Job_mode: Working status (FullTime 35%, Contract 33%).

Distribution

Usage

• Performing survival analysis to estimate employee tenure.
• Building classification models to predict employee attrition risk.
• Intermediate-level studies in employment trends and workplace behaviour.
• Examining the influence of various factors (e.g., job satisfaction, income, travel) on retention rates.

Coverage

License

Who Can Use It

• Data Scientists: For training machine learning models predicting attrition.
• HR Analysts: To identify key drivers of employee turnover and develop retention strategies.
• Academic Researchers: For studying employment patterns and workforce dynamics.

Dataset Name Suggestions

• Employee Survival Prediction Data
• IBM HR Attrition Analysis Set
• Workforce Retention Predictor
• Global Employee Exit Data

Attributes