Nate Silver on Finding a Mentor, Teaching Yourself Statistics, and Not Settling in Your Career

I had the pleasure to sit through a keynote at the Tableau Conference in Washington DC and the speaker was none other than Nate Silver.  It was a very good keynote and his book it a great read.  

I find it very interesting what he says about education and working with data.  I find the same thing.  I don't have a background in Stats or Math, however I feel I have a good intuition with data.  I have always loved numbers and working with them, but have never liked the mechanics of math or stats.  I think in todays age of technology, it is more important to have the intuition than the mechanical knowledge.

Again, I think the applied experience is a lot more important than the academic experience. It probably can’t hurt to take a stats class in college.

But it really is something that requires a lot of different parts of your brain. I mean the thing that’s toughest to teach is the intuition for what are big questions to ask. That intellectual curiosity. That bullshit detector for lack of a better term, where you see a data set and you have at least a first approach on how much signal there is there. That can help to make you a lot more efficient.

That stuff is kind of hard to teach through book learning. So it’s by experience. I would be an advocate if you’re going to have an education, then have it be a pretty diverse education so you’re flexing lots of different muscles.

You can learn the technical skills later on, and you’ll be more motivated to learn more of the technical skills when you have some problem you’re trying to solve or some financial incentive to do so. So, I think not specializing too early is important.

When I look for new hires i tend to find people who are smart and try to figure out their critical thinking.  The tools and the mechanical portion of data analysis and modeling can be taught, but it takes special people to have critical thoughts.  

I always say that an analysts job is not to report on the data, but to find the money.  The analyst that can take a dataset, find actionable insight and are able to articulate the findings are worth their weight in greenbacks.   

Very cool article from a great thinker.