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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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Headlines

Study: Salaries for early career data scientists decrease for first time

Salaries for early career data scientists decreased year over year for the first time in four years as did the percentage of early career data scientists with a Ph.D. while demand for data scientists continued to increase, according to a recently released Burtch Works’ 2017 salary study of data scientists. Salaries for more experienced data scientists generally held steady or increased slightly depending on an individual’s focus area, responsibility and geographic base, according to the report. Read more →

Generous health insurance plans encourage overtreatment, but may not improve health

Offering comprehensive health insurance plans with low deductibles and co-pay in exchange for higher annual premiums seems like a good value for the risk averse, and a profitable product for insurance companies. But according to a forthcoming study in a leading scholarly marketing journal, the INFORMS journal Marketing Science, such plans can encourage individuals with chronic conditions to turn to needlessly expensive treatments that have little impact on their health outcomes. This in turn raises costs for the insurer and future prices for the insured. Read more →

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