How to Build (and Keep) a World-Class Data Science Team
The culture of world-class data science teams is one in which team members (and their managers) are excited by what their teammates can do. Here’s how to create that kind of high-performing team.
To manage a first-rate data science or quant group, leaders need to build an engaging environment, get the team the resources it needs, and balance being involved while also staying out of the way.
Every team needs talented people. In data science, talented people need not only to be good at what they do individually but also able to challenge their colleagues to create effective new solutions to very hard problems.
How do you build a data science team to attract and retain this type of world-class talent?
Over the past twenty-five years, I’ve been lucky enough to lead a number of such teams, ranging in size from three to almost a hundred people. High-performing quant teams are characterized by high levels of output and extremely low levels of staff turnover.
In my experience, there are three main “jobs” that leaders need to take on to manage a first-rate data science or quant group: 1) Build an engaging environment; 2) Make sure the team has access to the resources it needs; and 3) Get their hands dirty — but stay out of the way.
1. Build an engaging environment.
Much of what motivates high-performing data scientists and quants, and what shapes a work environment for them, comes down to the outlook of their colleagues and the dynamics of their daily interactions. High-performing team members need to be comfortable giving colleagues their best ideas and collaborating to shape the most promising of these inchoate thoughts into real-world solutions, while willingly abandoning those that turn out to be less well-founded. The culture of world-class analytics teams is one in which team members (and their managers) are excited by what their teammates can do.
In such groups, team members err on the side of giving their colleagues too much credit for their work and ideas, rather than worrying whether their own contributions will be recognized. They are able to revel in discord and respect differences — which serve to test and refine ideas — while maintaining a sense of positive forward momentum.
An engaging environment is important not only for the staff but also for the company as a whole. For analytics teams to be effective, they must have continuity.