From the course: Data Science Team Lifecycle Management

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Develop an individual data scientist vs. the team as a whole

Develop an individual data scientist vs. the team as a whole

From the course: Data Science Team Lifecycle Management

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Develop an individual data scientist vs. the team as a whole

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- Data science tasks involve a combination, of statistics, coding, and machine learning, and there's some other skills too. Still, at some point as a manager, you'll be confronted with the challenge of developing people individually versus upgrading an entire team. Let's take a closer look at what goes into these decisions and why they're so important. Let's start by looking at the principles of building a successful data science team. The trick is hiring and developing people with the right amount of overlapping skills without being completely duplicitous. There are three main principles to this approach. The first is defining the roles and responsibilities of each team member. The second is providing adequate training and support for all team members. And the third is encouraging collaboration and communication among team members. The last point is critical. As your data science team grows, so must the team's…

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