This capstone project focuses on analyzing employee data to build a predictive model that provides valuable insights for the Human Resources (HR) department of a large consulting firm. The goal is to determine whether an employee is likely to leave the company using either a regression-based or machine learning approach.
This capstone project focuses on analyzing employee data to build a predictive model that provides valuable insights for the Human Resources (HR) department of a large consulting firm. The goal is to determine whether an employee is likely to leave the company using either a regression-based or machine learning approach.
As part of the project, I developed two key deliverables:
1️⃣ A One-Page Summary – A concise report designed for external stakeholders, summarizing the project’s objectives, methodology, key findings, and business impact.
2️⃣ A Complete Code Notebook – A well-documented Jupyter Notebook showcasing data preprocessing, exploratory data analysis (EDA), model development, evaluation, and key visualizations.
As part of my capstone project, I am working on an employee retention analysis for Salifort Motors, a fictional French-based alternative energy vehicle manufacturer. The company has over 100,000 employees worldwide, engaged in research, design, construction, validation, and distribution of electric and hydrogen-based vehicles.
The senior leadership team at Salifort Motors has tasked me with analyzing employee survey data to uncover key insights into workforce retention. My objective is to develop a predictive model that identifies employees who are at risk of leaving the company. This model will leverage critical factors such as department, number of projects, average monthly hours, and other relevant data points to generate actionable insights.
To tackle this challenge, I will use either:
- A regression-based model to quantify relationships between employee attributes and attrition likelihood.
- A tree-based machine learning model for a more complex, non-linear prediction approach.
This project will provide data-driven insights to help Salifort Motors' HR department implement targeted retention strategies. By identifying trends and risk factors in employee attrition, the company can make informed decisions to improve employee satisfaction and reduce turnover rates.
This capstone project not only enhances my expertise in data analysis, machine learning, and predictive modeling, but also serves as a strong portfolio piece to demonstrate my ability to solve real-world business challenges using data.