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There's always room for smart, hard working and creative thinkers in any field. Except maybe marine biology. But as in any lucrative field, e.g. law, you have a wide variety of capabilities and work quality. After 10 years in quantititative work (I got an MS in Applied Math before they were calling Statistics "Data Science") I can say that it's just a tough field to work in. Experience goes further than education, but education (yes, a real accredited graduate level education) is necessary. The most challenging aspect of DS isn't the technical aspects, it's being able to have a thick enough skin to not let the skeptical and reluctant engineering types upon who you depend to implement your brilliant models get under your skin and enough patience to explain and convince the skeptical and not too savvy business types who cut your checks, that their intuition is wrong and your math is right. And then of course, there's the inevitable boredom that comes with solving yet another mundane business problem with the simplest and least sexy tools. I'm not complaining, just saying that almost all STEM graduates turned DS I've ever worked with have a small hollow spot in their soul that burns with passion for the astrophysics or theoretical math problems they traded in for the perk filled corporate life.

3 easy steps to get a job in DS if you want them though: Grad Degree in Math/Stats/CompSci; work on a bunch of hard to predict problems and then publish and present them to your local meetup community to gain experience; learn engineering tools and devops and be about 90% as good a software engineer as your team's actual engineers (git, hg, IDEs, java, pig)... your brilliant models are way less important than being able to help the already overwhelmed engineering team make them work.




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