In August 2025, Andreas Fabisch expanded scikit-learn’s StandardScaler to support the Array API, enabling seamless operation across multiple array backends beyond NumPy. Working within the scikit-learn/scikit-learn repository, Andreas enhanced internal logic for data-type and namespace resolution, ensuring compatibility with diverse array implementations. The work included updating documentation to guide users on cross-backend usage and adding comprehensive tests to validate correctness and compliance. Using Python and leveraging skills in data preprocessing, machine learning, and testing, Andreas delivered a well-integrated feature that deepened scikit-learn’s backend flexibility. The contribution demonstrated thoughtful engineering and addressed a nuanced interoperability challenge.