DJ Patil explains the skills, tools and processes that make data science teams successful. The author explains the process behind building analytical teams at Facebook and LinkedIn.
Key takeaways
- Being data driven means using data creatively, measuring results and experimenting.
- Run competitions for external people and hire the best.
- “If you can’t measure it, you can’t fix it”
- Hiring data science teams. When hiring answer those questions:
Time: Would you survive with another person locked in a small room?
Trust: Do I trust you, will you trust me? Will you do all you can to give best results?
Communication: If we’re going to spend a tremendous amount of time together and if we need to trust each other, we’ll need to communicate.
- Every data project is a new experiment. Don’t treat it like an old product development team.
- Data Scientists, who are they?
Technical expertise: the best data scientists typically have deep expertise in some scientific discipline.
Curiosity: a desire to go beneath the surface and discover and distill a problem down into a very clear set of hypotheses that can be tested.
Storytelling: the ability to use data to tell a story and to be able to communicate it effectively.
Cleverness: the ability to look at a problem in different, creative ways.
Links:
- Building Data Science Teams: https://www.amazon.com/Building-Data-Science-Teams-Patil-ebook/dp/B005O4U3ZE
- Overview: http://radar.oreilly.com/2011/09/building-data-science-teams.html