7 Data Science Career Paths

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Interested in a career in data science? You’re in luck: there are thousands and thousands of jobs available for people who know what to do when it comes to analyzing data. The Harvard Business Review called it the “sexiest job of the 21st century”, but people often shy away from it because of the deep analytical skills it requires. Here are seven potential paths you can take to realize your ambition.

Getting a leg-up


Data science is new to the academic scene, at least in a pure form, but since New York University launched its Masters of Science degree in data science, other universities have started to follow suit. There’s a program at the University of California, Berkeley, which takes 20 months to complete, with the main curriculum all being taught online, for example. There are other programs listed here.

Girl throwing her cap at graduation

Because these degrees and programs are new, they’ll offer you a great competitive edge. Get yourself through one of these courses and you’ll have a head start in whatever path you follow.

Boot camps:

If you don’t want to go the traditional route, there’s a lot of boot camps out there just waiting to kick you into gear. They can be a pretty intense experience, but they focus on giving you a lot of skills and diving deep into the technical stuff. It can be a great way to network and get contacts as well, if you think that might be important to your career.



Data Management Professional:

If you want to work your way up through the ranks, so to speak, this option might be more your style. It’s usually an IT role, like the database management roles already available. You need to focus on your Apache, SQL and databases to get ahead here; data analysis won’t be important to your role.

Data Engineer:

Don’t want to focus on the analytics, and don’t fancy being a Data Management Professional? The data engineer role focuses on the infrastructure of big data. Again, you’ll need to know your databases and SQL. You’ll be doing a lot of design and implementation.

Business Analyst:

Business analysts actually have to handle the data collected and maintained by the infrastructure Data Management and Data Engineers put into place. You need to be able to work with data and get conclusions from it, and you’ll also need to be adaptable. You need to have a good knowledge of how to work with databases.

Machine Learning Researcher:

Machine learning researchers really start to manipulate the data in order to analyze it. They’re the ones who pull predictions from the data and make forecasts. You need to have a pretty broad base for this, so it’s the kind of job that keeps on changing all the time: you need statistics, programming skills, learning theory and a solid knowledge of algorithms.

Data-oriented Professional:

If you’re not scared of hard work and keeping your eye on a lot of different threads at once, this role might be for you. It combines aspects of all the other roles, depending on what’s necessary at the time. There’s a huge focus on the data, with how you draw conclusions from it being secondary to knowing the right way to draw conclusions from it at any given moment.

Graph on a computer screen

It’s worth remembering that you don’t just need to look at the private sector for all of these roles, though. Data science is just coming into its own in the public sector, and things are getting moving. Interested in working for the CIA? This might just be the path you want to take. Office of the Inspector General? You bet. Whatever interests you, there’s pretty certain to be something that will use your skills. It’s the era of Big Data, and we’re just beginning to see how powerful it is.


Have any questions about data science? Let us know in the comments and we'll get one of our data scientists to answer! 

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Dikirim 26 Jun, 2017

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