7 Recommendations for Data Science Leaders

After five years of working on different data teams in the game industry, I recently decided to join a startup in the finance industry. While many data teams were allocated large amounts of resources, it was usually challenging to actually put findings into production and have customer facing impact.

Based on my experience at Twitch, Electronic Arts, and Daybreak Games, I have the following recommendations for leaders of data science teams: 1. Set realistic expectations for the Data Scientist role 2. Provide a forum for sharing results 3. Define a process for productizing models 4. Encourage data scientists to submit PRs 5. Avoid Death by MBR 6. Provide a roadmap for how to level-up as an IC 7. Setup tooling for reproducible research. I’ll discuss each of these points in more detail below and highlight examples from my experience.

Author: Ben Weber


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