A few years ago, everybody was talking about the rock star technology job of the future: data scientist -- a unicorn who understood computer science, statistics, and how vertical businesses worked. These were rare professionals in high demand and so they commanded high salaries, got the best work/life balance, and were considered the "sexiest."
Thanks, in part, to new and improving open source and vendor-provided tools, the frenzied demand for these technology pros has gotten a little calmer, and salaries for data scientists and predictive analytics professionals have remained relatively steady over the past year. That's according to the annual salary survey for these professionals compiled by quantitative executive recruitment firm Burtch Works.
These tools "have made what used to be very complex and rigorous math and computer science problems into something that is more manageable and available to solve for a wider range of individuals," said Linda Burtch, managing director of the firm. She and Katie Ferguson, a partner at Burtch Works, presented the results in a webinar and in a written report this month. "While still far from point and click, these tools are maturing quickly, and this is having a positive impact on closing that talent gap in analytics," Burtch said. "But let me be clear. That gap is still very large."
These more sophisticated tools that have made analytics accessible to more workers represent one of the major trends that Burtch Works identified from this year's survey. Another major trend is a geographic expansion of the opportunities for data scientists (which Burtch Works defines as those who work with all types of analytics, including those that use unstructured and streaming data) and predictive analytics professionals (who Burtch Works defines as those who work on structured data).
Linda Burtch said that data science and analytics initiatives are growing quickly with opportunities across the country -- not just concentrated on the west coast like they were 5 or 6 years ago. In addition, these opportunities are not just concentrated in tech companies such as Google and Facebook anymore. Now there are opportunities in many vertical industries, including agriculture, education, law enforcement, weather, health, energy, and security, among many others. Early adopters tended to be centered in advertising tech and e-commerce, Burtch said. Now, there is movement toward "mission-driven" roles that have a societal or environmental benefit.
Burtch noted that she's seeing interest shift from hiring unicorns who can do it all to hiring specialists in a particular area of artificial intelligence or data science. For instance, an employer may be looking for a specialist in natural language processing (NLP) or computer vision.
A sampling of the numbers
Entry-level (level 1) predictive analytics professionals with a four-year degree can expect an entry-level base salary that averages $78,615 (with a median of $80,000). A master's degree won't make that much of a difference to salary at level 1 for predictive analytics pros who earn a base level salary that averages $80,737 (with a median of $80,000).
At the entry level, predictive analytics pros saw a salary increase of 4% year over year, Ferguson said. Level 2 and level 3 individual contributors each saw a 2% increase year over year.
Level 3 predictive analytics pros with a PhD earn an average base salary of $159,956 (with a median of $140,000).
The Burtch Works salary survey looks at salaries for 6 job experience levels -- levels 1, 2, and 3 individual contributors and levels 1, 2, and 3 managers. Within each level, the survey provides deeper detail based on the degree level -- bachelor's, master's, or PhD.
Predictive analytics pros with bachelor's degrees who are managers at level 1 earn an average salary of $127,759 (with a median of $124,000), and if they are at level 3 managers and have a PhD, they earn an average base salary of $271,643 (with a mean of $250,000). Predictive analytics managers at level 1 and level 2 saw no increase in salary year over year. Level 3 saw an increase of 4% year over year.
The survey provided separate sets of numbers for each levels for both predictive analytics professionals and for data scientists.
Data scientists at level 1 with a master's degree earn an average base salary of $92,222 (with a median of $90,000). Data scientists at level 3 with a PhD earn a base average salary of $177,020 (with a median of $180,000). Level 1 and level 2 data scientists saw no salary increase year over year. Level 3 data scientists saw a 1% salary increase.
For data scientists who are managers, those at level 1 with a master's degree earn an average base salary of $143,230 (with a median of $140,200). Data scientist managers at level 3 with a PhD earn an average base salary of $268,045 (with a median of $250,000). Level 1 and level 3 manager data scientists saw no salary increase year over year. Level 2 data scientist managers saw a 3% increase in salary year over year.
The full numbers are available in the report that can be downloaded from the Burtch Works blog.
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