I graduated from UC Berkeley with a degree in Statistics and Environmental Economics. Although I think that conserving the environment for the betterment of the human race in the long term is incredibly important, Statistics definitely beat out as a major. It's the shit. Now I work as a data scientist at Premise in San Francisco. I get to play with a bunch of really awesome time series; it's basically like data candy land. Also, there are board games.
As a side hobby, I enjoy making so-called art . I like trees. I enjoy playing chess, Scrabble, Settlers of Catan, and poker (Texas hold'em). I listen to audiobooks. I like Arrested Development and Game of Thrones. This week I got sick and watched House of Cards (approve). I like to boulder.
I grew up in Portland, Oregon. There, the sky isn't so dreadfully monochromatic all the time, and trees are everywhere. Bay area jobs are definitely cooler, though.
Graphs can show so much! Node and line sizes, colors, shapes, and placements (over time!) can all tell the stories of distinct variables! It's pretty hard to see trends that live in these multiple dimensions while staring at spreadsheets. So - especially when you can't understand the data you're working with in one gulp - don't just stare at spreadsheets: make pretty pictures, too! At least that's my viewpoint. Infographics rock (Why doesn't Obama's fiscal budget contain only text?! 255 pages of pure pdf text is pretty painful to swallow, especially when they take care to represent facts in ways that are not entirely enlightening and at least a little bit over-flattering to the administeration. Anyways. Back to the main point, things I like: tangents that come full circle).
Life goals of mine, because everyone on the internet should know:
- Create a website that initially just has a lot of informative graphs about government spending (primarily US), but eventually offers 'drill-down' interactive capabilities, well written explanations, and links to more information (discretionary budget inspiration).
- Read more books on theoretical and applications-based statistics.
- Learn more about machine learning; win (or nearly win) a Kaggle contest.
- Write a small booklet on some statist-y thing, and make it freely available.
- Work part time, or soley on my own projects.
- Travel (one can program anywhere!)
- Make a positive difference. Epsilon counts, but the bigger the better.
- Smile more