Linda Burtch, Managing Director at Burtch Works | 30+ years’ experience in quantitative recruiting

Since we’re now firmly planted in 2017 and predictive analytics & data science teams have likely set their hiring plans (for the time being), we decided to check in and see how the hiring market is looking this year.

Many of you are probably familiar with our quick “flash surveys” that we send out to our quantitative network with a question or two, and we used this method to gather some data from our network of hiring managers. For more detail about the survey, see note below.

What we found was that more teams are hiring at the beginning of 2017 than at the end of 2016. 89.5% of teams are planning some form of hiring in the first half of this year, compared to 84.3% during the second half of 2016. This includes teams who are hiring to add to headcount, teams that are backfilling positions left vacant due to attrition, and teams that are adding and backfilling.

When we looked further at teams that were expanding in some way (which includes teams adding only + those adding & backfilling), we found that more teams are growing overall. 75.6% are planning team expansion in Q1/Q2 2017 compared to only 66.7% in Q3/Q4 2016. No teams reported that they’re cutting back, although some did report that they have no intention to hire.

According to our analysis at the beginning of the year, the percentage of predictive analytics professionals changing jobs has increased each year since 2014. With 22.1% changing jobs in 2016, it’s not too surprising that the data shows so many teams backfilling empty roles!

In the chart below, you can see the breakdown of a few common industries as well as the overall figures:

A few of the notable trends we saw when looking at the industry breakdown were:

  1. Consulting firms are expanding the most (adding only + adding & backfilling), with Tech/Telecom/Gaming companies as a close second.
  2. Advertising/Marketing firms are doing the most backfilling (adding & backfilling + backfilling only), which suggests this is an industry with high turnover.
  3. Retail/CPG has the least companies expanding their teams, no surprise given the ongoing headlines of dire retail results.
  4. Financial Services has the most teams that are not hiring at all, likely awaiting upcoming regulatory changes.


We plan to continue monitoring shifts in the hiring market, so be sure to check back for updates. We’re also working on sharing data to update our research on salary increases analytics folks receive when changing jobs, as well as editing our always highly-anticipated data science salary study. You can download last year’s report for free here.

Let us know what you think in the comments, and if you have any thoughts on other topics for research feel free to drop us a line!


Since the survey refers only to the first half of 2017, the “adding” category refers to teams who didn’t anticipate having to tackle turnover during the next couple months, resulting in growth of the team. If the team was hiring because they are both adding to headcount AND contending with attrition, then they fall under “adding and backfilling”.

Want to learn more about data science and analytics salaries and hiring market trends? Watch the video below for insights from our 2019 salary study!


6 Responses to “2017 Analytics & Data Science Hiring Update Shows More Teams Expanding”

  1. Peter Jaumann

    Great insights!! A few comments……
    1. the distinction between [Hiring, Adding] and [Hiring,Adding & Backfilling] is confusing and not clear. Especially if one contrasts it to [Hiring, Only Backfilling] then.
    2. Advertising, marketing, mobile analytics does have a high turnover….reasons I have seen: expectations are too high, results are expected too fast, salaries are not high enough and they don’t hire the best candidates
    3. Retail: Really has the highest rates on [Hiring, Only Backfilling}. So there is a lot of opportunity there. I don’t think it has to do much with ‘dire retail results’. Remember, consumer confidence is high. People are retiring in that field and newly hired data scientists in retail are not creative enough, perhaps yet. And not enough emphasis on new, creative customer analytics that is much more holistic than ever. Technologies play a very important role here too as does agility and dynamics. And, retailers may not pay well enough yet.

    • sbosowski

      Thanks for your comments, Peter! I updated the post to include a note about the categories we used in the survey.




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