As data scientists, we have a top priority: delivering accurate insights. If you’re like me, a data scientist who’s also working on search (or any real-time application for that matter), you’ve got to manage two competing priorities that sometimes butt heads: accuracy and speed.

I’ll walk you through some of the things I’ve learned through trial and error as a data scientist in search, including tips on how to smooth out some of the friction that can pop up when you’re building a tool that demands cross-collaboration with other domain disciplines.

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