Data Science

2 Mutch Geek

[Cross-posted from ICanHazDataScience] I’ve been descending into a lot of Python hints lately, and not so much on the data analysis side of things.  Whilst I finish writing up an example analysis involving poo (yes, really!), here’s something I wrote a while ago to a young aspiring data scientist… What it takes to be a data scientist, most of all, is curiosity, persistence, intelligence and the ability to tell a story: that drive to understand what’s wrapped up inside the data, to learn whichever tools it takes to get that understanding, and the skills to explain it to others. It also helps to have a strong technical background, because we haven’t yet developed the user-friendly tools and training that non-technical data scientists need (we’re working on it!), so some knowledge of Bayesian statistics and things like text processing and – unfortunately – the ability to program in a language like…