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This post is an edited excerpt from our newly-released report, The Burtch Works Study: Salaries of Predictive Analytics Professionals 2018, compensation and demographic data of 1,791 PAPs is shared in this report, and it can be downloaded for free here.

If you’re interested in learning more about the implications of the trends discussed in this post, as well as several other trends impacting the analytics market, you can read our trend synopsis here.

2018 Predictive Analytics Salaries

Our salary studies report base salary variations of predictive analytics professionals, both individual contributors and managers, as well as the proportions eligible for a bonus, and the median and mean bonuses received. We also report how base salaries have changed since last year’s study. Finally, the report explains how salaries of predictive analytics professionals vary based on several characteristics including job level, industry, region, education, residency status, and gender.

The median base salary of individual contributors at level 1 is $76,750 and increases, based on job level, up to $130,000 for those at level 3. Over 79% of all individual contributors are bonus eligible, and the median bonus they received varies from $8,000 to $17,500 depending on specific job level.

Predictive analytics professionals in management roles earn higher base salaries, are more likely to be bonus eligible, and earn larger bonuses than individual contributors. Managers at level 1 (with 1-3 direct reports) earn a median base salary of $130,000, which increases to $240,000 for managers at level 3 (with 10 or more direct reports). More than 93% of all managers are eligible to receive bonus pay. Those at level 1 earn a median bonus payout of $19,050, increasing to $75,000 for those at level 3.

When compared to 2017 data, median base salaries at all job levels showed either no change or a single-digit percentage point change. For individual contributors at levels 2 and 3 and managers at level 1, median base salaries remained unchanged. For those at all other job levels, salaries showed single digit percentage changes indicating that salary bands are holding steady.

Industry Shifts in Predictive Analytics

Firms in the Financial Services and Marketing/Advertising sector together have typically comprised over 50% of the employers in our study sample. However, last year (2017) was the first year that their combined share fell below half to 45%, and this year their share fell again to 43%. This is likely due to use cases for predictive analytics diversifying and increasing in other industries.

For instance, over the past five years, the tech/telecom/gaming vertical has nearly doubled from 8% in 2014 to 14% in 2018. The growing number of companies with data-based products and services, as well as the increase in analytics team size at more established tech firms, likely accounts for this growth.

Who are Predictive Analytics Professionals?

At Burtch Works, the predictive analytics vs. data science distinction emerged a few years ago to separate the analytics professionals working with mostly-structured data vs. the subset of data scientists who were able to manage unstructured or streaming data. Historically, this has meant that data scientists have had the skills to use Python, machine learning/AI, Hadoop, etc., and generally have more coding skills than the other predictive analytics folks that we work with.

Because of the skill differences, this has also meant that data scientists have earned higher salaries than the predictive analytics professionals at the same level of experience. We’ve also observed key demographic differences, especially when it comes to which industries and regions employ more data scientists vs. predictive analytics professionals.

As one might imagine, over the past few years things have been shifting, with predictive analytics professionals picking up more data science tools/skills and the use of the “data scientist” term to encompass so many different types of data professionals, which have both muddied things a bit. We still observed a considerable salary difference between the two groups in our last data science salary report (data scientists earned anywhere from 3-36% more than predictive analytics professionals depending on job level), so we’re currently evaluating how the shifting definitions might affect our classification system moving forward.

 

Looking for More Information?

Want to learn more about current trends in the predictive analytics market? Read about the increase in early career professionals, our thoughts on salary bands remaining steady, and more, plus their implications for both analytics professionals and employers.

Want to see how predictive analytics salaries vary by industry, region, education, and more? Download our full report for free access to over 30 pages of information on salaries, bonuses, demographic data, and more.

2 Responses to “Predictive Analytics in 2018: Salaries & Industry Shifts”

  1. Paul

    The predictive analytics salary graphs would be much more informative if you segmented by type of professional (analyst vs data scientist or statistician, e.g.) and education (PhDs make considerably more than those with a BS). Unsegmented, it just throws everyone in together, so one really has no idea where one’s salary falls given the more important factors that go into determining salary.

    Reply
    • sbosowski

      Hi Paul,

      Thanks for your comment! Data scientists are actually the subject of their own study, this report focuses on predictive analytics professionals that primarily work with structured data. In the full report, you can see salaries segmented by job level and then education, region, industry, etc. This post is merely meant to be an overview of the full, 30-page report which can be downloaded at http://www.burtchworks.com/study

      Each report also goes into further detail about how we segment predictive analytics professionals from data scientists, etc.

      Hope this helps!

      Stacy

      Reply

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