Isaac Slavitt
Isaac is a co-founder and principal data scientist at DrivenData, Inc. He holds a master's in Computational Science and Engineering from Harvard’s School of Engineering and Applied Sciences and a BS in Operations Research from the U.S. Coast Guard Academy, and previously spent seven years as a Coast Guard officer serving in a variety of operational and quantitative roles.
Sessions
Data science as a professional discipline is still in its infancy, and our field lacks widespread technical norms around project organization, collaboration, and reproducibility. This is painful both for practitioners and their end users because disorganized analysis is bad analysis, and bad analysis costs money and wastes time. This talk presents ten principles for correct and reproducible data science inheriting from software engineering’s seven decades of hard-earned lessons as well as numerous experiences with data science teams at organizations of all sizes. We motivate these principles by looking at some hard truths about data science “in the wild.”