Jason Cherry is a data scientist and ML engineer with a decade of experience building production forecasting and uncertainty quantification systems. His current work focuses on spatiotemporal interpolation of Argo float profiles, developing open-source tooling to make interpolation uncertainty accessible to operational practitioners for the first time. He recently completed the MATE Center Floats program and is currently enrolled in mechanical engineering coursework at Spokane Falls Community College as part of an active transition toward oceanographic fieldwork. He has previously presented at PyData Denver on machine learning methodology. His Argo interpolation library is available at github.com/Calvinxc1/argo-data-interpolation.