Chi Chova developed comprehensive Propensity Score Methods documentation for the mixpanel/docs repository, focusing on enabling robust causal impact analysis and consistent terminology. Leveraging skills in data analysis, documentation, and statistical modeling, Chi detailed practical guidance for implementing propensity scores, including logistic regression usage and feature selection techniques. The work included a targeted update to the spell checker configuration in JSON to recognize domain-specific terms, reducing false positives and improving clarity. This documentation provides clear, replicable instructions for data scientists and engineers, enhancing onboarding and reducing misinterpretation of methodology, while maintaining a low maintenance footprint and supporting consistent implementation practices.