Brent Cohn
About
Brent Cohn is from San Francisco, California, United States. Brent works in the following industries: "Computer Software", "Internet", "Higher Education", and "Research". Brent is currently Data Science Manager: Experimentation and Causal Inference at Twitter at Twitter. In Brent's previous role as a Senior Data Scientist at Twitter, Brent worked in San Francisco Bay Area until Mar 2019. Prior to joining Twitter, Brent was a Data Scientist at Laboratory for Systems Medicine and held the position of Data Scientist at Boston. Prior to that, Brent was a Adjunct Professor at Tufts University, based in Boston from Aug 2014 to May 2015. Brent started working as Associate Scientist at GNS Healthcare in Cambridge in Nov 2013. From Jan 2013 to Nov 2013, Brent was Public Health Analyst at RTI International, based in Boston.
Brent Cohn's email is available on Finalscout.com free of charge. This database has a wealth of information on over half a billion business professionals and two hundred million companies.
Brent Cohn's current jobs
Experimentation and Causal Inference at Twitter. Our mission is to democratize the application of statistical inference to development at Twitter. To do this we research, develop, and implement methods to make it easier for developers to understand the effects of their work. Some recent projects include quantile testing for performance metrics, improving the detection of errors in experiment configuration, reducing variance in online experimentation, implementing new units of experimentation, and finding similar experiments to help experimenters set up the optimal experiment more easily. We're hiring, and for more info please see our job description linked below
Brent Cohn's past jobs
As a Data Scientist at Twitter, I worked on teams that forecasted revenue, modeled advertisers willingness to spend, and supported our online experimentation platform.
Applied machine learning & data analysis for Harvard professors Ziad Obermeyer (health policy) and Sendhil Mullainathan (economics). Work mentioned in Andrew Gelman's blog: Statistical Modeling, Causal Inference, and Social Science: http://andrewgelman.com/2016/07/09/causal-and-predictive-inference-in-policy-research/ Full paper available: https://www.cs.cornell.edu/home/kleinber/aer15-prediction.pdf
Designed and taught Health Policy and the Open Data Revolution, a full credit class offered in 2014. Syllabus: http://bco.hn/syllabus.html This class focuses on the application of data science techniques to open healthcare data. Students learned R, and created a healthcare related term project.