4 Core attributes of a data scientist
17 Jan 2016 - This is a post on my blog.
Note: I wrote this short post a few years ago and recently found it floating around. It seems more obvious now (and probably trite), but I thought it was still worth posting on the old 'net.
- Thinking statistically. Things tend to come in distributions. Understanding this make a huge difference in how (data) problems are approached. See #2.
- Strong grasp of the fundamentals. By having a strong base of math, stats, experimentation, and computer science, the job of the data scientist is much easier. For a specific problem, the fundamentals may not be enough, but they will get you very far.
- Curiosity. Data science is all about answering questions and pulling value out of raw, likely messy data. A data scientist must feel the need to really dig in and find out what the data can tell them. Curiosity can take you on some strange detours, but on the whole it pays off.
- Willingness to learn. Data science is a very broad field with a multitude if facets. No one can be expected to master all areas. Nonetheless, a data scientist must be willing to dive in and learn new tools, techniques, and domains to be most effective.