An answer in two parts:<p>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.<p>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.<p>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.
That really depends on the task at hand and for each case there are lots of similar tools, so let's consider just the most frequently used.<p>Daily I'd say RStudio, Excel, Tableau, PowerPoint. Either I'm coding in R or I'm presenting.
Development - Jupyter IDE for Python
Text Editor - Sublime Text
Knowledge Base - Stackoverflow
Visualization - Matplotlib + Excel Charts
Presentation - PowerPoint
Much of the data I analyse has a spatial/geometric/geographic component and for that I wouldn't want to do my job without FME. In fact it's probably may one of my all time favorite pieces of software.<p>Otherwise jupyter with numpy and all the other great python libraries is where I spend much of my time.
Out of interest, is everyone using Spark/Hadoop/etc because you need to and/or you chose to or another reason? IMO, legit use cases seem to me relatively sparse.