David Black

David Black is a data scientist with extensive experience in natural language processing, machine learning, and deep learning algorithms. David has worked at Clarigent Health, where they transformed unstructured linguistic and acoustic data into structured data to detect warning signs of mental health risks. David also developed new models that identified language features associated with mental health conditions and explored the impact of demographics, linguistic characteristics, and text classification on mental health predictions. Before that, they worked as a data and research scientist at The Henry M. Jackson Foundation for the Advancement of Military Medicine and as a project manager at Givaudan, where they led cross-functional teams to plan and execute flavor development research. David has a background in senior leadership roles for beauty and pet care at Procter & Gamble. Currently, David Black works as a data scientist at Claritas.

David Black holds a Ph.D. in Experimental Psychology from the University of Cincinnati. David also has an M.A. in Experimental Psychology and a B.A. in Psychology from the same university. David completed a Post Doctorate in Kinesiology and Exercise Science from the University of Michigan. In 2018, they obtained a certification in Data Science from Johns Hopkins University.