Worked on expanding scikit-learn’s StandardScaler to support the Array API, enabling seamless operation across multiple array backends beyond NumPy. This involved enhancing internal logic for data-type handling and namespace resolution, ensuring compatibility with diverse array implementations. Updated documentation to clearly reflect the new cross-backend capabilities and provided comprehensive tests to validate correctness and compliance. The work, contributed to the scikit-learn/scikit-learn repository, focused on robust integration of the Array API within the data preprocessing pipeline. Utilized Python and testing frameworks to deliver a maintainable solution that broadens StandardScaler’s applicability in machine learning workflows involving various array libraries.