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Case Study - HR Employee Attrtion Dataset

Context

McCurr Health Consultancy is an MNC that has thousands of employees spread across the globe. The company believes in hiring the best talent available and retaining them for as long as possible. A huge amount of resources is spent on retaining existing employees through various initiatives. The Head of People Operations wants to bring down the cost of retaining employees.

For this, he proposes limiting the incentives to only those employees who are at risk of attrition. As a recently hired Data Scientist in the People Operations Department, you have been asked to identify patterns in characteristics of employees who leave the organization. Also, you have to use this information to predict if an employee is at risk of attrition. This information will be used to target them with incentives.

Objective

  • To identify the different factors that drive attrition
  • To build a model to predict if an employee will attrite or not

Dataset Description

The data contains information on employees' demographic details, work-related metrics and attrition flag.

  • EmployeeNumber - Unique Employee Identifier
  • Attrition - Did the employee attrite or not ?
  • Age - Age of the employee
  • BusinessTravel - Travel commitments for the job
  • DailyRate - Data description not available
  • Department - Employee's Department
  • Distance FromHome - Distance from work to home (in KM)
  • Education - Employee's Education. 1-Below College, 2-College, 3-Bachelor, 4-Master, 5-Doctor
  • EducationField - Field of Education
  • EnvironmentSatisfaction - 1-Low, 2-Medium, 3-igh, 4-very High
  • Gender - Employee's Gender
  • HoulyRate - Data description not available
  • JobInvolvment - 1-Low, 2-Medium, 3-High, 4-Very High
  • JobLevel - Level of job (1 to 5 )
  • JobRole - Job Roles
  • JobSatisfaction - 1 Low, 2-Medium, 3-High, 4-Very High
  • MaritalStatus - Marital Status
  • MonthlyIncome - Monthly Salary
  • NumCompaniesWorked - Number of ompanies worked at
  • Over18 - Whether the employee is over 18 years of age ?
  • OverTime - Whether the employee is doing overtime ?
  • PercentSalaryHike - The percentage increase in the salary last year
  • PerformanceRating - 1 - LOw, 2-Good, 3-Excellent, 4-Outstanding
  • RelationshipSatisfaction - 1 Low, 2-Medium, 3-High, 4-Very High
  • StandardHours - Stamdard Hours
  • StockOptionLevel
  • TotalWorkingYears
  • TrainingTimeLastYear - Number of training attended last year
  • WorkLifeBalance - 1 Low, 2-Medium, 3-High, 4-Very High
  • YearsAtCompany
  • YearsinCurrentRole
  • YearsSinceLastPromotion
  • YearsWithCurrentManager

In the real world, you wwill not find definitions for some of your variables. It is the part of the analysis to figure out what they might mean .