Worked on the astropy/astropy repository to enhance the reliability of scientific data analysis workflows by addressing a bug in the sigma clipping process. Focused on preserving the input data mask when the grow parameter is used, the solution involved replacing np.copy(data) with data.copy() to ensure correct mask propagation. Added a regression test to verify this behavior, supporting robust masked-data analyses and downstream pipelines. The work was implemented in Python, leveraging skills in data analysis, scientific computing, and testing. No new features were released during this period, but the improvements strengthened data integrity and test coverage for core functionality.