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Careers in Big Data

6 years ago

ID: #45811

Business Description

For this ComputingEdge issue, we asked Naren Ramakrishnan—professor of engineering and director of the Discovery Analytics Center at Virginia Tech University—about big-data career opportunities. Ramakrishnan’s research interests include mining scientific datasets in domains such as systems biology, neuroscience, sustainability, and intelligence analysis. He was a co-guest editor for Computer’s April 2016 special issue on big data. ComputingEdge: What careers in big data will see the most growth in the next several years? Ramakrishnan: With this space maturing, more than seven of 10 organizations in the US are expected to have an in-house data science team by the end of this year. Demand for data scientists will grow in technical areas like deep learning, as well as in fields such as healthcare, the Internet of Things economy, finance, manufacturing, educational innovation, sustainability, and forecasting. You can keep track of what’s going on in data science forums such as KDnuggets (www.kdnuggets.com). ComputingEdge: What would you tell college students to give them an advantage over the competition? Ramakrishnan: Remember those courses you thought were boring and had nothing to do with real-life, like differential calculus, Bayesian statistics, graph theory, and linear algebra? They are the foundations of data science today! So spend time honing your fundamentals in college. It will prepare you for advanced courses and careers in areas such as deep learning, computer vision, and sensor mining. It’s also important to develop a portfolio of your data-analytics and visualization code, perhaps hosted on a GitHub page. Many prospective employers want to see examples of your big-data and data-analytics skills. ComputingEdge: What should applicants keep in mind when applying for big data jobs? Ramakrishnan: Just as data-science applications are varied, so are the job titles, responsibilities, and expectations. Find out how data science fits into a potential employer’s organizational structure. Do they have a CDO (chief data officer) or CIO (chief information officer)? Does data science play a supporting role or is it an integral part of the way they do business? How many business units within the organization rely on data science? These questions are important to understand how you will fit within the organization and how the organization will fit within your career objectives. Software Tool Overview Video ComputingEdge: How can new hires make the strongest impression in a new position?

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