9 reasons why you’ll never become a Data Scientist
Disclaimer: This story is not meant to discourage you. Rather, it should serve as a long hard look in the mirror.
So you’re enthusiastic about Data Science, you’ve read a couple dozen blog posts and completed a few online classes. Now you’re dreaming of making this your career. After all, it’s the sexiest job of the 21st century, according to Harvard Business Review.
But despite your enthusiasm, Data Science might not be for you. At this moment in time, you’re holding too many illusions and false stereotypes.
Now, your task is simple: Remove the things that hold you back! And you’ll be surprised at how fast you move forward.
You have a master’s degree in a quantitative field, or maybe even a Ph.D. Now you want a head start in Data Science.
But have you ever used a shell before? Have you felt the intimidation that can come from command-line interfaces when you stumble upon errors? Have you ever worked with big databases — on the scale of Terabytes?
If you answer one of these questions with no, you’re not ready yet. You need some real-world experience and build some real projects. Only then will you encounter the type of problems that you’ll face every day as a Data Scientist. And only then will you develop the skills to solve them.
Congratulations on your degree. Now get cracking on the hard work.
Have you ever invested an entire weekend in a geeky project? Have you ever spent your nights browsing GitHub while your friends were out to party? Have you ever said no to doing your favorite hobby because you’d rather code?
If you could answer none of the above with yes, you’re not passionate enough. Data Science is about facing really hard problems and sticking at them until you found a solution. If you’re not passionate enough, you’ll shy away at the sight of the first difficulty.
Think about what attracts you to becoming a Data Scientist. Is it the glamorous job title? Or is it the prospect of plowing through tons of data on the search for insights? If it is the latter, you’re heading in the right direction.
Only crazy ideas are good ideas. And as a Data Scientist, you’ll need plenty of those. Not only will you need to be open to unexpected results — they occur a lot!
But you’ll also have to develop solutions to really hard problems. This requires a level of extraordinary that you can’t accomplish with normal ideas. If people constantly tell you that you’re off your rocker, you’re heading in the right direction. If not, you’ll need to work on your craziness.
This, of course, requires some boldness. Once you let out your eccentricity, some people will scratch their heads and turn their back on you. But it’s worth it. Because you’re being true to yourself. And you’re igniting the spark of awesomeness that you need as a Data Scientist.
Don’t get me wrong. Textbooks and online classes are a great way to get started. But only to get started! You need to work on real projects as soon as possible. Of course, there is no point in building a Python project without being able to code a single line in Python. But as soon as you’ve built a modest foundation, get active.
Learning by doing is key. Start building your GitHub portfolio. Take part in some Hackathons and Kaggle competitions. And blog about your experiences.
Everybody can do textbooks. To be a Data Scientist, you must do more.
You’ve subscribed to a couple of online courses on Data Science and are reading a few textbooks. Now you think that once you’ve mastered those, you have learned enough to break through in Data Science. Wrong. This is yet the beginning. If you think you’re learning a lot now, think about how much you’ll be learning in three years.
If you end up as a Data Scientist, you’ll be learning ten times more than you are now. It’s an ever-changing field where new technologies are constantly needed.
