Leading Data Science Teams

Chapter 3. Running a Team That Provides Value

This is almost painfully stale to say, but the success of your data science team entirely depends on how well the people on it can fulfill their roles. That your team members have clear, achievable goals and the resources to execute them matters more than what technology you choose to execute your code on, or the types of models you choose to train. Data scientists have all sorts of different backgrounds and differences in how they think and what they want to do. As a leader, it’s your job to create an environment where the data scientists can succeed. There are thousands of books out in the world on how to manage people, so instead of purely providing guidance around management broadly, this chapter will focus on the specifics of leading data scientists.

As a data science leader, you want your data scientists to be contributing value to your team and your organization. Value is a difficult term to define with data science because it can be so abstract and disconnected from the amount of work put in. A summary graph of data that takes five minutes to make one day might end up being more valuable to an organization than a complex machine learning model that a whole team spends months on. Because of that, let’s explicitly define contributing value.

A data scientist is contributing value to the team if they are creating and finishing code, reports, or other deliverables that:

• Solve the requested task

• Are straightforward to maintain ...