In the October 2012 edition of the Harvard Business Review, Tom Davenport and DJ Patil deemed the sexiest job of the 21st century to be “data scientist.” These individuals are responsible for manipulating Big Data at companies to glean insight and improve business operations.
These professionals are in high demand for a number of industries, from pharmaceuticals to insurance. The McKinsey Global Institute estimates that the demand will outstrip supply for analytical professionals by up to 190,000 in 2018, so it's a hot market to enter.
Here are four tips from data experts on how to prepare for a career in data science:
1. Be Ready for the Long-Haul in Academics: Focus on obtaining undergraduate, masters and doctorates in applied mathematics, computer science, machine learning, physics, econometrics or other interrelated disciplines. Ideally, learn as much about the theory behind programming, statistical models and popular computer algorithms as possible.
2. Don’t Forget About Academia After School: Even when your educational career is over, keep in-touch with happenings within academic research. Subscribe to the academic journal of your choosing, such as the IEEE PAMI or the Journal of Machine Learning Research.
3. Work on Project Management Skills: Unlike in academia, the business world often affords a team of programmers to help with coding and development projects. As important as it will be to expertly manipulate a dataset, it will be equally important to be able to delegate tasks and manage team projects so they are completed on time and correctly. Read books on various management styles and find the method that works best for you.
4. Participate in Open-Source Projects and Coding Contests: It’s important to keep your skills sharp, as data scientists often use a wide variety of languages, tools and applications every day. To hone your skills, there are a number of web resources online (such as bigdatauniversity.com) to obtain more information on a variety of programming languages. To test your prowess in the “wild,” look for collaborative projects in web forums, or participate in data contests on websites such as Kaggle.com.
Michael Koploy is an Analyst for the Software Advice website. For more in-depth information on the topic of data science careers, check out 3 Career Secrets for Aspiring Data Scientists.
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