November 8, 2017

Standards Effort Seeks to Redefine ‘Data Scientist’

George Leopold

(Mini bear/Shutterstock)

Da-ta Sci-en-tist, noun, a person employed to analyze and interpret complex digital data, such as the usage statistics of a website, especially in order to assist a business in its decision-making.”

That’s one generally accepted definition of data scientist. An industry group focused on skills gaps, along with high-profile companies isn’t satisfied, embarking instead on a standards effort designed to define what it means to be a data scientist.

The skills group, General Assembly, announced this week it is launching a Data Science Standards Board that will define the skills required to be a data scientist. Among those enlisting in the standards effort are Bloomberg, Booz Allen Hamilton and Spotify.

Despite soaring demand for data skills—estimated at 2.7 million new data science jobs by 2020—”there isn’t a standardized way of defining, certifying or even quantifying the number of data scientists in the workforce,” the partners asserted in announcing the standards initiative on Wednesday (Nov. 8).

Along with a skills shortfall, data science also suffers from a diversity gap, the partners said, noting that, “data science is among the least diverse fields in tech.”

The new standards board will seek to identify and define data science skills and ultimately establish performance criteria to certify the data science workforce.

“Pervasive skill and equity gaps in data science reflect two related challenges: lack of unbiased tools to help employers quantify and understand the skill sets that matter, and inadequate transparency for job-seekers trying to understand what employers are looking for,” Jake Schwartz, CEO and co-founder of General Assembly, noted in a statement announcing the effort.

The resulting standard assessment could be used to predict job performance while matching skills with industry data science requirements, the group said.

The industry standards initiative parallels other efforts to bridge the big data skills gap. In October, for example, the National Science Foundation awarded grants that would fund two national data science workshops. The workshops are designed to develop curriculum “anchored in the actual practice of data science work,” organizers said. The curricula materials, including course modules and exercises, will be publicly available.

Meanwhile, the number of graduate level data science programs also is growing at U.S. universities, many sponsored by tech companies looking to hire data scientists.

Countering at least some of these trends, an annual salary survey released last summer by executive recruiter Burtch Works found that “some data scientists are also opting to skip the PhD as a faster route to the workplace, to capitalize on the numerous opportunities available.”

Presumably, the new standards group would take into account these supply-and-demand trends as it works in the age of AI to define evolving data science skills.

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