There is an ever-growing amount of data generated in all areas of life — from retail, transport and finance, to healthcare and medical research. Coupled with the high demands and remuneration of becoming a data scientist, on top of analysing and working with large datasets to address the underlying challenge faced, what is it exactly required out of a data scientist? Here are 3 ways to think like and hopefully help you become a data scientist?
1. Be creatively curious, keep challenging the status quo
As a data scientist, you write your own questions and answers. Data scientists need to be naturally curious about the data that they’re looking at, and approach them creatively with solution. Much of data science is not the analysis itself, but discovering an interesting question and figuring out how to answer it.
2. Be suspicious
A primarily reason why it’s really hard to replace a data scientist with a machine, is that a data scientist will tell you what’s important and what’s outright fake. This persistent skepticism is healthy in all sciences and is especially necessary in a fast-paced environment where it’s too easy to let a spurious result be misinterpreted.
3. Just try NOW, even if you’re unsure of the outcome
Instead of planning when you should start, start typing some codes, or pen out your thought process on how to solve a specific problem. You don’t need to wait till you master python, or java. This is applicable to any learning behavior but it’s especially true in data science. Be sure you start trying it from the very first day you start learning. It’s very easy to put off the actual learning by just reading about the complex world of data science, how it “should” be done.