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Network World - After months of high unemployment and a still-wobbly economy, any good news from the jobs market is going to get some traction. But even that doesn't seem to fully explain the attention surrounding a suddenly very "in" job title: data scientist.
According to CNN, data scientist is one of the best new jobs of 2012, and an article in the Harvard Business Review called it the "sexiest" job of the 21st century.
The allure surrounding this role is in direct correlation with the general market's interest in big data and analytics -- tools of the trade for data scientists, who are tasked with unearthing meaningful correlations within ever-mounting data volumes and turning them into profitable business insights.
What's more, there is often a unicorn status imbued on people who fit this multifaceted position, which blends computer science, advanced quantitative concepts, business domain knowledge and communication skills. With demand for data scientists exceeding supply, salaries for these workers range in the six figures, according to Matthew Ripaldi, senior vice president at Modis, a staffing firm.
Recruiters also agree that the data scientist position is fast-growing, even if the number of job postings is not yet staggering. "When we started looking at this position two years ago, there were just eight postings, and now there are 42," says Tom Silver, senior vice president for North America at job search site Dice.com. "Forty-two out of 83,000 jobs is not huge, but I would suspect postings to grow even more in the future."
With all the attention, it's only natural that people with any background in data and computing might wonder, who are these people, and could I become one? We've tried to answer some of the most basic questions here.
The answer to this deceptively simple question depends on who you ask. A widely accepted definition comes from Hilary Mason, chief scientist at Bit.ly: someone who can obtain, scrub, explore, model and interpret data.
Neil Raden, CEO at Hired Brains, goes a bit deeper, categorizing data scientists into two groups.
Type I - are true scientists who research and create algorithms and methods, publish papers and actively participate in their discipline's communications. These individuals are found most often in research, academia and organizations, where new methods and algorithms are the core of the enterprise (think Google, Amazon, Wall Street), Raden says.
Type 2 - the group more often referred to in today's hiring market -- are not scientists but practitioners, Raden continues. These are experts in statistical and mathematical modeling and development, who understand and employ quantitative methods, as well as design, test and deploy models.
Jacob Spoelstra, global head of R&D at Opera Solutions, also distinguishes between what many people broadly categorize as data scientists and the work he and others do at Opera, a provider of predictive analytics as a service.