I used 2025 Stack Overflow Annual Developer Survey Results. Stack Overflow is a platform for developers to ask questions and share knowledge. Its annual survey is designed to capture the developer experience, and it is the longest-running and most comprehensive study of its kind. The 2025 survey contained questions on learning and career, tech and tech culture, community, and AI. It received 49,000+ responses from developers across 177 countries.
I chose this dataset because burnout is a growing concern in the tech industry, often going undetected until it affects performance and retention. Analyzing developer survey data can help organizations predict which employees may be at risk and identify the factors most likely to contribute to burnout.
This project was completed entirely in Python. I began with exploratory data analysis to examine the dataset's structure and identify features most relevant to burnout risk, then standard preprocessing steps such as handling missing values and encoding categorical variables. From there, I applied two classification algorithms, logistic regression for its interpretability and random forest to capture more complex patterns in the data. Model performance was evaluated using standard classification metrics, and feature importance outputs were used to surface the strongest predictors of burnout risk among developers.
[More coming soon...]