Download the dataset below to solve this Data Science case study on HR Analytics. (Dataset Source: Kaggle)
HR Analytics: Case Study
Sometimes companies experience high rates of employee attrition when a significant number of employees leave the company within a period of employment. In such cases, the main concern of the HR department is the negative impact of attrition on the company’s productivity.
Here is a dataset containing information about the company’s employees. This dataset was submitted by Pavan Subhash at Kaggle. Below are all the features in the dataset:
- Age: The age of the employee;
- Attrition: Whether the employee has left the company or not;
- BusinessTravel: The frequency of business travel;
- DailyRate: The employee’s daily rate of pay;
- Department: The department in which the employee works;
- DistanceFromHome: The distance between the employee’s home and workplace;
- Education: The highest level of education attained by the employee;
- EducationField: The field in which the employee’s education is focused;
- EmployeeCount: A count of the employees in the company;
- EmployeeNumber: A unique identifier for each employee;
- EnvironmentSatisfaction: The employee’s level of satisfaction with their work environment;
- Gender: The employee’s gender;
- HourlyRate: The employee’s hourly rate of pay;
- JobInvolvement: The employee’s level of involvement in their job;
- JobLevel: The level of the employee’s job within the company;
- JobRole: The employee’s job role;
- JobSatisfaction: The employee’s level of satisfaction with their job;
- MaritalStatus: The employee’s marital status;
- MonthlyIncome: The employee’s monthly income;
- MonthlyRate: The employee’s monthly rate of pay;
- NumCompaniesWorked: The number of companies the employee has worked for in the past;
- Over18: Whether the employee is over 18 years old or not;
- OverTime: Whether the employee works overtime or not;
- PercentSalaryHike: The percentage increase in the employee’s salary from the previous year;
- PerformanceRating: The employee’s performance rating;
- RelationshipSatisfaction: The employee’s level of satisfaction with their relationships at work;
- StandardHours: The standard number of working hours per day;
- StockOptionLevel: The employee’s stock option level;
- TotalWorkingYears: The employee’s total number of years working;
- TrainingTimeLastYear: The number of hours the employee spent on training last year;
- WorkLifeBalance: The employee’s level of balance between work and personal life;
- YearsAtCompany: The number of years the employee has been working for the company;
- YearsInCurrentRole: Number of years in the current role;
- YearsSinceLastPromotion: Number of years since last promotion;
- YearsWithCurrManager: Number of years with the current manager;
Use this data to analyze the relationship between the characteristics of employees and their attrition status to develop a predictive model that can identify which employees are most likely to leave the company.
