Stop Making Data Scientists Do Systems

In this webinar with Emily Curtin, Senior Machine Learning Engineer at Mailchimp, we’ll discuss how many organizations are lacking in a practical understanding of the Data Scientist persona from a UX perspective. By defining what Data Scientists are good at, and more importantly what they’re not good at, we as MLOps professionals and organizational leaders can build on that understanding and let Data Scientists do their best work.

• The best tools for Data Scientists are low/no-systems, not low/no-code.
• Velocity comes from good tooling; quality comes from good incentives.
• Infrastructure abstraction should be a top priority for MLOps professionals.