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Interactive computing with Jupyter Notebooks has transformed the state of the art of scientific research computing. Users can perform a multitude of computational tasks in real time, including data cleansing, analysis, visualization, and postprocessing, with Jupyter Notebooks. Additionally, the ability to write and execute code and include supporting text and images in the same document has made it popular for use in scholarly articles and teaching. These capabilities complement the batch computing services provided by high-performance computing centers exposed through traditional science gateways. However, integrating Jupyter into science gateways and other advanced computing ecosystems introduces new challenges related to scalability, collaboration, and reproducibility. In this article, we discuss the Scalable Interactive Computing (Scinco) project, an open source platform for scalable, reproducible, interactive scientific computing designed to be run in academic computing centers and incorporated into science gateways. We describe the prime features, architecture, deployment choices, and challenges of Project Scinco. [ABSTRACT FROM AUTHOR]