My current gig.
Was the first Chief Data Scientist of the US Department of Commerce and served as part of the leadership team of the Commerce Data Service, a new data startup team within the Office of the Secretary of Commerce.
Collaborated with Georgetown University's new program in data analytics/science to advise program faculty on strategic efforts, host hands-on sessions on applied issues related to the practice of data science, and mentor students on the emerging field of data science. Teach a graduate-level class on data science and machine learning for public policy.
I was selected to serve as a White House Presidential Innovation Fellow, working with the National Aeronautics and Space Administration (NASA) and the White House Office of Science and Technology Policy on the President's Climate Data Initiative.
As an extension of Mayor Bloomberg's data-driven push, I had the opportunity to be the first Director of Analytics for the New York City Fire Department. It was the first data science office in the nation's largest fire department. A key part of the work at FDNY was to develop FireCast, an experimental predictive risk engine that was able to predict fire risk with a high degree of accuracy.
In my off hours, I've worked on operations research projects to understand vaccine uptake, supply chain, and medical issues in Africa.
During the Bloomberg Administration, I was among the first of a new wave of advanced statisticians and data scientists to enter NYC government. I led projects tackling citywide priorities such as data-driven response after Hurricane Sandy to lawsuit outcome prediction to welfare fraud detection. My project portfolio spanned the Mayor's Office of Operations and the Center for Innovation through Data Intelligence in the Office of the Deputy Mayor for Health and Human Services.
I cut my technical teeth as an econometrician at an international economic and management consultancy working on large scale economic, infrastructure, transport and environmental investments. Most of my efforts focused on forecasting, prediction/scoring, estimation methods, spatio-temporal approaches, sampling design