Dan Sweeney is a skilled data scientist and advisor with leadership experience, currently serving as an Advisor for the Global Energy Transformation Programme at Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. Dan previously worked as a Senior Data Scientist for REEEP, focusing on improving outcomes for off-grid energy customers in Africa, and held a similar role at GEICO, where they employed statistical and machine learning techniques to guide business decisions. Earlier in their career, Dan served as a Communication Systems Officer in the United States Air Force and worked as a MultiFamily Modeling Associate at Freddie Mac while completing a master's degree in Statistics from George Mason University. Dan earned a B.S. in Mathematics from William & Mary and has consistently used quantitative techniques to impact strategic decisions across various industries.
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