I’m a Duke University grad with 2 years of experience scoping data science projects and building machine learning models to solve real-world problems. Currently, I work as a Data Scientist at Enigma Technologies. Enigma provides the content, tools, and expertise to empower organizations looking to make sense of the world through data. Before Enigma, I worked for the Federal Reserve Board of Governors building statistical models and algorithms to analyze data for U.S. monetary policy, financial regulatory policy, and economic research.

I’m also extensively involved with DataKind, a data-science non-profit. DataKind brings together data scientists and engineers with leading social change organizations to collaborate on cutting-edge analytics and advanced algorithms to maximize social impact. Currently, I’m the Technical Lead on a four person team working with Stand For Children, an organization dedicated to ensuring that all children, regardless of their background, graduate from high school prepared for, and with access to, college or career training.

Previously, I led a 30-person team to analyze and provide data driven recommendations to improve young adult employment and education programs in Philadelphia. Before that, I co-built and deployed machine learning models to optimize the Red Cross’s national campaign to install 2.5 million smoke detectors across the United States.

As of March 2017, the smoke detector campaign has saved over 200 documented lives.