How important is diversity on a data science team?

(soft upbeat music) - How important is diversity in the data science team? Like, people from different backgrounds, people with different academic skills. Do we want a wide diversity, a wide range, or do we want people who are like-minded? - You want people who are like-minded in attitude of chasing down answers, understanding things. But you want to have extraordinary diversity of talent. In the beginning days of LinkedIn, if you looked what the team's title was, it was called the A-Team, the Analytics Team, and the reason was that it was partly homage to the old 80s show. The A-Team is like, if you could find them and hire them, they will solve your problem, and the thing is like, if we take on a project, we will solve it, we will find a solution. But part of that was also there was a sub-tagline which said, it's literally, if you said it's not rocket science or brain surgery, but that's OK, we still got it covered. And the reason why is we literally had both a rocket scientist and a brain surgeon on our team. And I kid you not, we had a neurosurgeon on the team who, as it turned out, did not like neurosurgery after a little while, but loved working with data. And so, quit being a neurosurgeon to join our team and developed a huge amount of the analytics infrastructure that supported the data science team. Why is that so critical? Well, you need people that are coming from all these different ways to provide perspective. My experience at the White House, one of the greatest joys was, if I had a problem, not only could I call someone like Francis Collins, who helped decode the human genome, but I could go to the person like Cesar Chavez's granddaughter, Julie Chavez, and ask her a question. So you had this incredible diversity of skills and people with life experiences around the table that led you to much richer abilities to look at a problem and find awesome creative solutions. (soft upbeat music)