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Analytics Magazine

Inside Story: Data scientists’ salaries

Burtch Works, an executive recruitment agency specializing in big data and data science talent, recently released a couple of surveys that offer interesting insight into the data science job market, as well as the preferred modeling language/statistic tool for analytics professionals.

In its 2017 salary survey of data scientists, Burtch Works reported that salaries for early career data scientists decreased over the past 12 months. That may come as a surprise to companies struggling to find qualified candidates, as well as to freshly minted data scientists with high expectations, but there’s a logical reason for the finding. According to the study, big data hype is causing more data science hopefuls to enter the field, and the increase in supply is decreasing salaries at the junior end. Meanwhile, some data scientists are opting to skip the Ph.D. and go for a master’s degree as a faster route to the workplace, to capitalize on the numerous opportunities available.

Burtch Works also conducted a “flash survey” of more than a thousand data scientists and predictive analytics professionals to ascertain their preferred stat tool among SAS, R and Python. Among the findings:

  • Open source (specifically Python) support is highest in tech/telecom sector, which employs 41 percent of data scientists.
  • SAS preference is higher in more regulated industries such as pharma and financial services.
  • Data scientists (working with unstructured data) prefer Python at 69 percent.
  • Predictive analytics pros (structured data) prefer R (42 percent) and SAS (39 percent) almost equally.

I met Linda Burtch, founder and managing director of Burtch Works, at the INFORMS Conference on Business Analytics & O.R. in Las Vegas earlier this year. She was a panelist on “Growing an Analytics Team,” one of many great sessions at the conference. Linda offered plenty of insight, including this gem: More and more data scientists and other analytics professionals are listing “storytelling” among key skills on their resumes.

Which brings us to this issue of Analytics magazine. Along with articles on dark analytics, dark data, agriculture analytics and risk management amid global terrorism, the issue includes a lighter fare entrée by Esther Choy, president and chief story facilitator of the business communication training and consulting firm Leadership Story Lab. The title: “Data storytelling: No more criticism sandwiches.” Enjoy.

– Peter Horner, editor
peter.horner@mail.informs.org

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