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Jason Shumake has extensive experience in data science, statistical analysis, and experimental design. Jason is currently serving as the Director of Data Science at Aiberry, Inc., where they use AI technology to analyze patient data and deliver real-time risk scores and health insights to healthcare providers. In addition, they work as a Consultant for Botberry, an AI tool for mental health assessment, where they oversee the training and validation of machine learning algorithms.

Previously, Jason worked at the Institute for Mental Health Research (UT Austin) as a Data Scientist, providing statistical consulting, developing data pipelines, and managing databases. Jason also served as a Research Assistant Professor at the University of Texas at Austin, where they led a multiyear research project, supervised a team, and conducted data analysis for various publications.

Before that, they worked as an Adjunct Professor at Texas State University, teaching statistics and helping grad students with their research projects. Jason also served as a Postdoctoral Fellow at the Texas Consortium in Behavioral Neuroscience, conducting brain research and developing behavior prediction models.

Jason's career began with a Humboldt Fellowship in Germany, where they conducted scientific research projects. Overall, their work experience showcases their expertise in data analysis and research project management.

Jason Shumake holds a doctorate degree in Neuroscience and Quantitative Psychology, which they obtained from The University of Texas at Austin from 1998 to 2005. Prior to that, they completed their Bachelor of Science degree in Psychology from Birmingham-Southern College between 1993 and 1997. Additionally, they have several certifications in various fields such as Clinical Trials Design and Interpretation, Algorithms: Design and Analysis, and Intermediate Proficiency in German. These certifications were obtained through online platforms such as Coursera and the Goethe Institut.