Burnout Analysis and Classification Model

Context: a startup focused on burnout prevention and the improvement of organizational well-being through data-driven approaches.

Objective:To build a predictive model capable of analyzing questionnaire data and behavioral indicators, classifying burnout levels, and supporting preventive decisions for HR and management.

Key Activities: Dataset design and definition of relevant features
Development of supervised machine learning models
Model validation and results interpretation
Integration of the model into the platform’s product workflow

Outcome / Value: A scalable system for burnout risk classification, providing concrete decision support for organizations.