People Analytics – BRI Hackathon

This repository contains notebooks developed for the People Analytics competition held during the BRI Hackathon.

Project Overview

People Analytics leverages machine learning to help HR departments predict employee performance using historical KPI data.

In this competition, participants were required to build a machine learning model capable of accurately predicting whether an employee would be classified as a "Best Performer" in the upcoming year.

Objective

Using the provided dataset, the goal of this project is to:

Predict whether an employee will be categorized as a Best Performer (1) or Not Best Performer (0).

Workflow

• Define problem and business objective
• Import libraries and dataset
• Perform data understanding and descriptive analysis
• Handle missing values
• Perform feature selection
• Conduct feature engineering
• Train and evaluate machine learning models

Dataset Description

Below is the description of the variables used in the dataset:

• job_level – Employee job level
• job_duration_in_current_job_level – Duration in current job level
• person_level – Employee personal grade level
• job_duration_in_current_person_level – Duration in current personal level
• job_duration_in_current_branch – Duration in current branch
• employee_type – Employee category (Relationship Manager Type A, B, or C)
• employee_status – Employment status (Permanent/Contract)
• gender – Gender
• age – Year of birth
• marital_status_married (Y/N) – Marital status
• number_of_dependents – Total number of dependents
• number_of_dependents_male – Number of male dependents
• number_of_dependents_female – Number of female dependents
• education_level – Education level
• GPA – Grade Point Average
• year_graduated – Graduation year
• job_duration_as_permanent_worker – Duration as a permanent employee
• job_duration_from_training – Duration since training period
• branch_rotation – Number of branch rotations
• job_rotation – Number of job position rotations
• assign_of_otherposition – Number of additional assignments
• annual_leave – Annual leave taken
• sick_leaves – Sick leave taken
• best_performance – Best performance status (1 = Yes, 0 = No)
• avg_achievement_% – Average yearly achievement percentage against target
• last_achievement_% – Achievement percentage in the last quarter
• achievement_above_100%_during3quartal – Number of times achievement exceeded 100% in the last 3 quarters
• achievement_target_1 – Target achievement category 1
• achievement_target_2 – Target achievement category 2
• achievement_target_3 – Target achievement category 3