Data Science Churn Rate Analysis: Project Overview

• Develop a model that analysis the user's churn rate and help answer following questions-

1. Who are the users most likely to churn?
2. Why do users churn?
3. When do users churn?

• Scraped over 1000 job descriptions from glassdoor using python and selenium
• Engineered features from the text of each job description to quantify the value companies put on python, excel, aws, and spark.
• Optimized Linear, Lasso, and Random Forest Regressors using GridsearchCV to reach the best model.
• Built a client facing API using flask

Overview on Waze

Waze’s free navigation app makes it easier for drivers around the world to get to where they want to go. Waze’s community of map editors, beta testers, translators, partners, and users helps make each drive better and safer. Waze partners with cities, transportation authorities, broadcasters, businesses, and first responders to help as many people as possible travel more efficiently and safely.

You’ll collaborate with your Waze teammates to analyze and interpret data, generate valuable insights, and help leadership make informed business decisions. Your team is about to start a new project to help prevent user churn on the Waze app. Churn quantifies the number of users who have uninstalled the Waze app or stopped using the app. This project focuses on monthly user churn. In your role, you will analyze user data and develop a machine learning model that predicts user churn.

This project is part of a larger effort at Waze to increase growth. Typically, high retention rates indicate satisfied users who repeatedly use the Waze app over time. Developing a churn prediction model will help prevent churn, improve user retention, and grow Waze’s business. An accurate model can also help identify specific factors that contribute to churn and answer questions such as:

Who are the users most likely to churn?

Why do users churn?

When do users churn?

For example, if Waze can identify a segment of users who are at high risk of churning, Waze can proactively engage these users with special offers to try and retain them. Otherwise, Waze may simply lose these users without knowing why.