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Data Scientist and Data Engineer, Novice Epidemiological Modeler

John is a data scientist and data engineer that has built a career trying to quantify human behavior in actionable ways. He was an early employee at Poptip, where he worked on real-time data processing of huge volumes of social media data and hierarchical bayesian modeling. After its acquisition by Palantir, John worked on building products to optimize decision systems with flexible constraints specified in real time and where data feedback was delayed or not available at all. He then spent three years as the lead data engineer and data science at Predata, a startup aiming to measure human behavior on the internet in order to understand and anticipate global events and financial markets. He now spends his time contracting in a variety of fields from travel tech to HPC and VFX, and has his own early stage startup building technology for hearing loss. Prior to a February 2020, it had been a decade since John had substantial exposure to literature about public health, epidemiology, genetics, or virology. While he has done his best to get up to speed with the state of the art, he makes no claims to be an expert on epidemiology. He believes his biggest assets to the success of this project are in the ability to switch contexts between the big picture and the details, his expertise in building data engineering systems, and his relentless ambition.
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