Scaling is hard. Scaling data science is extra hard. What does it take to run a sophisticated data science organization? What are some of the things that need to be on your mind as you scale to a repeatable, high-throughput data science machine? Erik Andrejko, VP of Science at The Climate Corporation, has spent a number of years focused on this problem, building and growing multi-disciplinary data science teams.
In this video, we discuss what is critical to continue building world-class data science teams. We also discuss the practice of data science, the scaling of organizations, and key components and best practices of a data science project.