Ask HN: Data scientists, what tools do you use the most on a daily basis?

Daily I'd say RStudio, Excel, Tableau, PowerPoint. Either I'm coding in R or I'm presenting.

The software tools: For me, PyCharm and Jupyter for development, Dask for data preprocessing, Tensorflow, Theano, and various scipy libraries for ML, as well as helpers such as PyMC3 and Edward for probabilistic programming.

The important tool: a PhD in applied mathematics that taught me how to think originally and creatively about problems, to abstract and codify them with mathematics, and to approach them numerically and computationally.

I suspect that the answer you were looking for is the first set of tools. This set is extremely nice to have; the second set, at least for me, is essential.

I find it a bit disheartening that this is how you read my response to OP's question. The denizens of HN may in general disapprove, but I believe my education to be one of the most important factors in doing my job. I don't think it's fair to respond with thinly-veiled accusations of elitism, especially when I explicitly tried to also give him or her a "practical" answer.

> Nevertheless, 80/20 (80% solution in 20% time) does wonders with the right set of tools and a rudimentary appreciation of applied maths, 80/20 being often what businesses really need.

In some cases, you're right, but more and more often I see people assuming that they've found the "80% solution", when in reality it's something like a 30 or 40% solution. My personal experience is that with many problems, a bit of thought shows you that many seemingly simple problems are hiding both a lot of complexity and a lot of potential - and I've seen real money left on the table because of a failure to recognise this.

My opinion is that conceptualising the problem in the first place is what allows you to see really what an "80/20" solution looks like, and in my case I don't think I would be able to do that without my most potent weapon: my mathematical education.

Not every problem is like that: sometimes a simple, out-of-the-box solution does work really well, and solves a concrete business need. My point is that when this is about the limit of what you can do, you don't really know whether your problem is in this class or not.