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Q: What’s missing in data analysis job descriptions these days? A: Data analysis.
When people talk about shortages of analytics talent, I’m suspicious. Although analytics has had a lot of media attention over the past few years, a lot of organizations still don’t do a heck of a lot of analysis, and don’t seem to be moving in that direction.
Of course, analytics offers real benefits to business, and the volume of data available is growing fast. Yet, data analysis scales very nicely. You may have twice the data now that you had a year ago, but that doesn’t mean you need twice as many data analysts.
Still, some people tell me they desperately need analytics talent and can’t find it. They seem so sincere. And then, I read the job descriptions.
I read one of these today. It called for a long list of requirements, such as knowledge of six programming languages plus UNIX operating systems. All of this is valuable stuff, but it’s what wasn’t mentioned that got my attention: there wasn’t a word about knowledge of data analysis. No mention of say, statistics or operations research. Nothing about analytics process.
Most of the analytics job descriptions I see these days are just as bad. The people who write these lists of job requirements either a) want programming talent rather than analytics talent (and that is often the case) or b) do not know how what skills a data analyst actually needs.
If things are that far off the mark before anyone has even applied for the job, I shudder to think of the interviews. I fear there will be brain teasers, coding tests, or something worse.
Do you want to attract analytics talent? Do you sincerely want the help of people who can turn your data into concrete and actionable information to support business decisions? Treat analytics job applicants like peers instead of fraternity pledges.
Invest some time and effort preparing for the interview. Ask yourself some tough questions:
- What do I want analytics to do for this organization?
- Am I prepared to make decisions based on the results of thoughtful data analysis?
- Am I willing to provide analysts with guidance about the business, explaining business problems, goals, and limitations? Can I ensure that analysts will have access to people and other resources as needed to do the job?
- What is my past experience of analytics? What has gone well, or poorly, in that experience?
- What career path can the data analyst expect in my organization?
When you think that way, you see the data analyst as a respected partner, not a programming machine. You approach the interview as a conversation, rather than a test. The more tough questions you ask of yourself, the better you’ll understand what you want to ask of your applicants, and the more you will be motivated to really listen to what they have to say.
Still not sure what to ask in the interview? Then use the candidates resume as a starting point. Don’t quiz, and don’t focus on those long lists of keywords skills. Instead, focus on something the candidate has done, a project that interests you. Ask for a walk through with questions like these:
- What problem was the project meant to solve?
- How did you work through this with people in complementary roles, such as executives, database administrators and subject matter experts?
- What parts took the most time? What did you find most challenging? What was most satisfying?
- Tell me how you approach analytics process.
- How did you share results – written reports, presentations, new applications…?
If the answers are good, you’ll soon add plenty of your own questions.
Interviews are for discovering what the applicant knows and can do. If you want to attract real analytics talent, treat your applicants as respected peers. Don’t test, discover.
