Some people are excellent at one thing, like professional athletes. Some people are average— weekend athletes who can keep up with a pick-up basketball game in the park. here are players who are really good shooters, there are players who are really good defenders. There are also the players who do well in multiple parts of their game, but aren’t excellent in just one area—I like to think of myself as one of those kinds of people.*

As a kid, I was really bright and very interested in becoming a TV meteorologist.I followed this dream into college when I realized I was very good at calculus, physics and thermodynamics. I was very good at developing and communicating forecasts, but not excellent at it. This—and graduating in the middle of the recession—led me to another path: teaching.

I ended up teaching (including my time as a substitute and as a student teacher) for 7 years. I was very good at explaining chemistry and physics concepts to unmotivated art school kids, and I was very good at handling the ups and downs of dealing with teenagers 193 days a year, but I was not excellent at it. This (and barely surviving wave after wave of budget cuts) led me down yet another path. This is what brought me to data analysis.

I know I have a very good analytical mind and I excel at communicating technical concepts. I know I have good coding skills and am able to keep items organized. I love the big picture and the minute details. I feel like being very good at all these skills is vital for a data scientist, a job that requires a lot of being “very good” at a number of things but doesn’t require being “excellent” at one thing. I think I’ve found a perfect fit for me.

*Despite being tall my whole life (an experience littered with “Do you play basketball?” until everyone realized I wasn’t getting a Division 1 scholarship), I’ve only been a decent player the last few years. Sometimes it takes a little longer for those skills to come out. And yes, I would like to play sometime.</sub>