Contributed to the scikit-learn/scikit-learn repository by enhancing feature selection and documentation capabilities. Developed support for sparse feature importance in RFE and SelectFromModel, enabling these tools to handle estimators that provide feature importance as sparse matrices or arrays. This was achieved by introducing an importance_getter callable and implementing comprehensive tests for both sparse and dense scenarios. Improved the discoverability of the Local Outlier Factor algorithm by adding a direct documentation link in the user guide. Collaborated across teams to coordinate API coverage and testing efforts, utilizing Python, data science, and machine learning expertise to deliver robust, maintainable solutions.