The corporate world has shifted to data which is why the demand for data professionals has skyrocketed for the past few years.
Data science encompasses a wide area of expertise. The most common jobs in data science include data scientist, data analyst, business intelligence analyst, data architect, and data mining engineer. Mindset also matters if you want to enter the data science industry. One of the most important thing to keep in mind is that data science is not for everyone. If you do not know how to code, that’s fine. The thing that can make or break your career relies on how badly you want it. You can learn things, but willpower comes from within.
Before you step into the data science world, here’s how to prepare.
Learn the Difficult Things First
It sounds like a pessimist to call it “difficult” so instead, let’s call it “challenging”. And what are the challenging things you need to learn? Knowledge in a computer language (specifically Python or R), strong statistical mathematics skills, knowledge in deep learning, and business know-how are on top of the list. Even if you need to have the right attitude to land your dream job, hard skills still matter. Although you just need the basics of machine learning, statistics, and programming, it doesn’t hurt to go the extra mile just to be sure.
Conduct Consistent Research
Just researching once would not give you in-depth knowledge of the world you’re trying to get into. If you are eager to work in data science, you have to step up your researching game. Each day a new job post is published, especially in the tech industry. From there, you can take notes on the things they require from applicants, and those requirements are exactly what you need to start your career in data science. See how data science leaders talk about their craft and how you can incorporate yourself into their world as well.
Offer Pro Bono or Discounted Services
Your chances of getting hired becomes higher when you have a portfolio. And because you’re new to the industry, it’s pretty rare to come by an opportunity that pays well. So money aside, how much do you want to advance in your newly-found career? Never underestimate clients when you’re just starting out. On the other hand, don’t sell yourself too short either. Volunteer your services to a non-profit organization or bid low rates on freelancing sites. Either way, you’re ready to jumpstart your data science portfolio.
For starters, there are available books, articles, and video tutorials with hands-on training online. Taking on a new career path is not easy – it takes dedication and patience. While you’re at it, don’t forget to prioritize your well-being and not overdo it as well.
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