A survey of 600 data scientists found that many are "exhibiting high levels of work-related stress", with more than a quarter reporting they were "heavily stressed." Steve Ranger, the UK editor-in-chief, TechRepublic and ZDNet suggested, "The research identified ten psychometric profiles present in the data scientist community. While technical, analytical and logical skills still dominate in the profiles, other skills such as project management, creativity and good communication skills are also present." The report said organizations must better identify and define what they need from data scientists.

Big Data Startup, the online Big Data Knowledge Platform, identified positions that did not exist before the phrase or concept of Big Data was formulated including Chief Data Officer (a new C-level position) along with Big Data Visualizer and Big Data Solutions Architect.

Perhaps there is a price for the stress. Ann Bednarz reported in NetworkWorld, the corporate appetite for big data is translating into rising salaries for IT pros. In its 2014 Salary Guide, Robert Half Technology (RHT) identifies 10 IT jobs in the data/data administration field. The highest paying is data warehouse manager, with starting salaries ranging from $115,250 to $154,250. The biggest raise goes to business intelligence analysts, who can expect a 7.4% boost this year.

Elizabeth Dwoskin reported in the Wall Street Journal this August, "While a six-figure starting salary might be common for someone coming straight out of a doctoral program, data scientists with just two years' experience can earn between $200,000 and $300,000 a year, according to recruiters." Dwoskin went on to cite Josh Sullivan, who leads a 500-person data-science group at the consulting firm Booz Allen Hamilton Holding Corp, "Anyone with "data science" in his or her job title on a LinkedIn page is going to get 100 recruiter emails a day."

A careful examination of the precise skillsets required varies greatly. Some recent positions describe the big data scientist skills as having a solid understanding of statistical modeling, predictive analysis, machine learning, and data mining. Other job descriptions ask for an understanding complex business challenges, designing scientific solutions, manipulating large data sets, using cutting edge machine learning or statistical processing.

More often the position of big data scientist is advertised by a manager of human resource who is unclear about the tasks, skills, and core competencies needed to fulfill the position. Vague job descriptions describe the role leveraging Big Data mining and analysis strategies to optimize current operations, provide business insights, improve targeting, and maximize return on investment. The employers in the industry drill down to specific technology competency may have a better handle on the experience needed for the position, such as a strong engineering background in technologies including Scala, Python, Java, Big Data, and Hadoop. Experience in data analysis techniques and advanced SQL Server, R, and Tableau are frequently requested. The big data scientist positions are not being filled quickly with demand far exceeding supply. This allows people with these targeted skillsets to name their salary and working environment.

Despite all these high paying data scientist jobs, the real test of Big Data will only be known with an attached bottom-line economic impact. Spotting trends and patterns in data are valuable skillsets if the ability to recognize behavior patterns is commercialized and monetized. Companies are going to evaluate the P&L of these high-paying positions in 2015 - 2018 and ask what they received for their big data compensation packages. If those salaries are correlated to profitability then one can expect a rosy future for the job scientists, even if the stress does not appeal to all who enter the arena.