Kevin is a Senior Data Scientist in The Lab @ DC. He plays a leading role in envisioning and implementing The Lab’s data analytic standards and protocols, executing (and wherever possible automating) important data analytic tasks, and guiding the use of machine learning, as well as developing entirely novel uses of data that maximize how much we can learn from the District’s vast amount of administrative data.
Kevin brings years of experience in a wide array of data analytic topics, ranging from system and security architecture to advanced statistical techniques to the development of novel predictive models and commercial tools. As the Principal Data Scientist at Knewton -an education technology company- Kevin developed and implemented methods for drawing real time and retrospective insights from massive, complex datasets, and was especially involved in bridging the divide between classic techniques like psychometrics with the modern techniques of machine learning. Kevin also has experience explaining such complex topics to diverse audiences, ranging from small academic seminars to high school students. His work has appeared in such diverse venues as the Journal of Combinatorial Theory and Educational Data Mining, and some of his popular projects have been written up in the Washington Post and Daily Kos.
Kevin earned a B.S. in mathematics from University of Michigan and a Ph.D. in mathematics from Princeton University. He enjoys pondering the potential regression discontinuity experiments he could do near his home at the border of Wards 1 and 2.
Talk Data to Me
This monthly speaker series brings together industry experts to discuss how data is changing the way businesses run and people live.