A detection model that used use user behavior data to predict which users are likely to churn. The model uses machine learning to predict the likelihood of a user churning and provides insights into the factors that contribute to churn.
Used Tools: Python, Polars, Scikit-learn, PowerBI, Spark, Mixpanel, Sentry, NewRelic.