How to Prepare for a Career in Data Science

Susan Hall

Though software engineering generally leads those Top 10 lists of jobs with the greatest demand and salaries, data scientists increasingly are right up there.

Arnab Chakraborty, director of HP Global Analytics, told Economic Times that data scientists can command a 30 to 40 percent premium in compensation over software engineers. It's not clear whether that's true, but demand certainly is driving salaries up. And it's not clear where all the required talent will come from.

Laura Kelley Houston, vice president at IT consulting and staffing firm Modis, told Network World that data scientists earn $110,000 to $140,000 around the country. But managers, too, are needing to develop these skills.

Steve Miller, co-founder of OpenBI, writes at Information Management about the debate within his company about the best major for data scientists, including advocates for computer science, information systems, as well as math, statistics and economics.

Ovum writes of the skills required:

Data scientists should have an aptitude not only for hard programming  skills in SAS, SPSS, and R, but also for understanding how to display or  visualize information in a business context. Data science is therefore a business practice, rather than a defined set of statistical or  technology competencies.

New degree programs are popping up to meet the surging demand, though the University of North Carolina remains a leader in the discipline. Its Institute of Advanced Analytics has been offering a master of science in analytics since 2007. Northwestern University offers an online master's program in predictive analytics.

This fall, Harvard will offer a new master’s degree program in computational science and engineering (CSE), which it touts as having "a curriculum broader than typical for master’s degrees in computational science, anchored by core courses in both computer science and applied mathematics and embracing a wide range of applications, including the social sciences in particular.”

Miller said he likes this curriculum, which has an emphasis on machine learning, for its promise to prepare students in programming, computation, numerical methods, optimization, statistics and applications to the social, health or natural sciences. He's hoping in the future it will be offered online.

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