Data scientists and analysts in healthcare, insurance, HR analytics, or subscription SaaS need to model time-to-event outcomes (patient mortality, customer churn, employee attrition, loan default) correctly, handling censored observations and time-varying covariates that standard regression and classification methods cannot accommodate.