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Ryan Stoddard, PhD has a diverse work experience in data science, chemical engineering, and electrochemistry. Ryan began their career in 2011 as an Electrochemistry Simulation Intern at Robert Bosch GmbH. In 2012, they worked as a Chemical Engineer at Argonne National Laboratory, where they conducted research on ultrathin nanorods fabrication, magnetic nanotubes for nanofiltration, and other projects. In 2013, they worked as a Researcher at NTNU. From 2014 to 2015, they worked as a Research Scientist/Engineer at the University of Washington Bioengineering. From 2015 to 2020, they worked at the University of Washington as a Chemical Engineering PhD Student, where they were awarded a $1.5M DOE grant to apply machine learning to analyze high throughput experimental measurements relating perovskite features to stability and optoelectronic quality. In 2018, they were an Advanced Data Science Option Student at the University of Washington eScience Institute. In 2019, they were a Data Science PhD Intern at Seattle Genetics, where they leveraged Machine Learning to aid research and development and build production level models. In 2020, they began working at Tignis, Inc. as a Data Scientist and Data Science Manager.

Ryan Stoddard, PhD obtained their Doctor of Philosophy in Chemical Engineering with an Advanced Data Science Option from the University of Washington in 2020. Prior to that, they earned a Master's degree in Chemical Engineering from the University of Washington. Ryan also obtained a B.S. and B.M. in Chemical Engineering and Music Technology from Northwestern University.