Blog post

Why Your Analytics Hire Is So Elusive

By Christi Eubanks | August 03, 2015 | 0 Comments


Yesterday I was scanning LinkedIn job postings for “marketing analytics” positions, because I like to stay on top of who’s hiring and at what level. My search returned 26,000 openings, so if you’re wondering – literally everyone.

Gartner’s survey data reveals that most companies are looking to grow their analytics teams (subscription required). The Bureau of Labor Statistics agrees (see statistics, market research analyst, computer scientist), and the old but often quoted MGI study projects a particularly troubling analytics talent gap by 2018. Marketing analytics skills – including “Statistics” at No. 1 – dominated LinkedIn’s hottest skills for 2015 list. The market is on fire!

What is a desperate hiring manager to do? We’ll save salary, cultural fit, career development, and org charts for another day. Let’s address the issues at the top of the hiring funnel first.

Here are three reasons why your job post isn’t bringing in the right candidates:

Your ideal candidate is a unicorn. Admit it. You and/or the recruiter took a bunch of LinkedIn posts and genetically engineered your perfect, beautiful quant baby with skills you didn’t even know you needed. Requirements include:

  • MS or PhD* in computer science, data science, statistics, or other quantitative field; MBA preferred
  • Progressive experience managing teams in a corporate environment, preferably 5 years in my industry [only PhDs who work for competitors need apply]
  • Mastery of every digital marketing analytics platform known to man and Google Analytics certification, and Facebook, plus advanced statistics and modeling skills, plus every BI tool/stats package, plus all the coding languages, but most importantly SQL, knowledge of ad serving tech and experience managing AdWords campaigns is a major plus [is that all?]
  • Experience with enterprise data architecture, relational databases, NoSQL and Hadoop, Hive, Spark [this is getting into data engineer territory]
  • The usual: strong written and verbal, persuasive, high EQ, ability to navigate a matrix organization [can we just stick to math matrices]
  • Enthusiasm for building weekly dashboards in PowerPoint

Data scientists are related to, but not the same as statisticians, who are not all versed in web analytics, which is not SEM, though all of the above can probably handle some SQL, and none would pick .ppt as their favorite medium. There are three or four different experts rolled into this one position, but none of them are going to apply for this job.

Great analysts are life-long learners; find one with potential and give her a chance to do some of it on the job.

*NC State’s Michael Rappa talks about why PhDs don’t scale.

You’re hiring at the wrong level / not promising fulfilling work. “Not afraid to get your hands dirty” is always a red flag. “Roll up your sleeves” is its ugly cousin. Experienced analytics people assume some level of janitorial data work, but they want to spend the majority of their time on tasks that leverage their interests and expertise. No self-respecting data whiz wants to let his advanced modeling muscles atrophy while he tries to muster an “enthusiasm” for weekly dashboarding. A bona fide data scientist will cost you nearly as much as an entry-level Ferrari these days…you don’t buy one just to drive to the grocery store.

You’re looking in the wrong place. LinkedIn is a must, but it’s not enough. To land the most elusive analysts you might have to meet them in their natural habitats (no, not basements). Analytics conferences or industry associations are an obvious place to recruit. You could start exploring analytics topics on Quora. Providing some of your data for a graduate class project – I did that with NYU Stern one semester – or posting a challenge to a competition site like Kaggle (legal permitting) could be an option. Some companies even buy lists of top students from MOOCs.

Are you looking to build your analytics team this year? Don’t get discouraged, but do increase your chances by homing in on the right match with a well targeted job post.

If you are a client, you might want to check out our toolkit for finding a Director of Marketing Analytics, and stay tuned for more research on analytics teams.

The Gartner Blog Network provides an opportunity for Gartner analysts to test ideas and move research forward. Because the content posted by Gartner analysts on this site does not undergo our standard editorial review, all comments or opinions expressed hereunder are those of the individual contributors and do not represent the views of Gartner, Inc. or its management.

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