Passionate about data science for social and economic advancement.
April (she/her) is a data scientist with 10+ years of experience across tech, consulting, and research. She genuinely believes more organizations could be improved through a more scientific approach to solving problems, and using technology to scale those solutions. Her area of expertise is in causal inference methods for measuring the impact of policies, campaigns, and strategic decisions.
Most recently at Lyft, April led the development of models that measure the effects of strategic pricing policies in order to optimize long-term growth and profitability goals. Prior to Lyft, April led a research & development team at Civis Analytics, which developed software to measure and optimize campaigns, used across US presidential elections, nonprofits, and Fortune 500 companies.
April graduated from the University of Chicago with a BA in Economics, where she also conducted research in labor economics. She is passionate about leveraging data science to help inform social and economic policies that advance equity, justice, and climate change goals. She grew up in Brooklyn, NY and most recently has been residing in San Francisco, CA.