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.

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