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Although many articles have been written lamenting the current talent shortage in analytics and data science, I still find that the majority of companies could improve their success by simply revamping their current hiring processes.photo-1441804238730-210ce1c2cc00

We’re all well aware that strong quantitative professionals are few and far between, so it’s in a company’s best interest to be doing everything in their power to land qualified candidates as soon as they find them. It’s a candidate’s market, with strong candidates going on and off the market lightning fast, yet many organizational processes are still slow and outdated. These sluggish procedures are not equipped to handle many candidates who are fielding multiple offers from other companies who are just as hungry (if not more so) for quantitative talent.

Here are the key areas I would change to make hiring processes more competitive:

  1. Fix your salary bands – It (almost) goes without saying that if your salary offerings are outdated or aren’t competitive to the field, it will be difficult for you to get the attention of qualified candidates. For up-to-date compensation information on analytics, marketing research, and data science professionals, check out Burtch Works’ salary studies, which are all available for free and have served as a key resource for our clients.
  1. Consider one-time bonuses – Want to make your offer compelling but can’t change the salary? Sign-on bonuses and relocation packages are also frequently used, especially near the end of the year, when a candidate is potentially walking away from an earned bonus; a sign-on bonus can help seal the deal.
  1. Be open to other forms of compensation – There are plenty of non-monetary ways to entice Quants to your company. I wrote an article for Forbes which talked about what else motivates quantitative professionals, like having the latest tools, solving challenging problems, organization-wide buy-in for analytics and more. Other things to consider could be flexible work arrangements, remote options or other unique perks.
  1. Pick up the pace – Like I said before, talented analytics professionals are rare, and the chances that qualified candidates will be interviewing with multiple companies are very high. Don’t hesitate to make an offer if you find what you’re looking for – your competitors won’t.
  1. Court the candidate – Just as you want a candidate who stands out from the pack, a candidate wants a company that makes an effort to stand apart also. I once had a client from Chicago send an interviewing candidate and his family pizzas from a particularly tasty restaurant here in the city. I can’t say for sure that the pizza was what persuaded him to take the company’s offer, but a little old-fashioned wooing never hurts.
  1. Button up the process – Just as it helps to have an expedited process, it also works to your benefit is the process is as smooth and trouble-free as you can make it. This means hassle-free travel arrangements, on-time interviews, and quick feedback.

 

Imagine if you were a candidate interviewing with multiple companies, would you be more impressed by the company who did all of the things on this list, or the company who didn’t?

If you fix it, they will come.

 

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

8 Responses to “If You Want to Hire Data Scientists, Fix Your Hiring Process”

  1. Mark

    Great article. To your list I would add “Ask questions from all stages of the data mining process”. When I was looking for a position, I judged companies based on the questions they asked. If all they did was ask textbook questions on modeling and programming, I knew they didn’t really understand data science and that’s a recipe for disaster (just wait until you see the “cure cancer” caliber assignments they give you once you start working there). In all my interviews, only a few asked me questions on data preparation or to explain a complex concept in layman’s terms. No one put me through a mock dialog with a client to see how I’d determine the *true* problem to be solved, no one asked me questions on exploratory data analysis, and no one asked me about methods of data visualization. Pizzas are fine at all (unless they have pineapple, in which case they are the tool of the devil), but want data scientists fear most is working for a supervisor who doesn’t understand data science.

    Reply
  2. Dave Wilson

    Beisdes the compensation aspect and if there is a restraint to it – other offerings could compensate for this. People want flexibility in work hours, times and work location. An analyst’s best and most productive work is usually outside of the office when there are less distractions. That can be said for many other occupations as well. Offer flexible start times and occasional remote working environments. You may be quite surprised that compensation isn’t at the top of the list.

    Dave

    Reply
  3. Priya Sarathy

    i agree on points of Dave and Mark. To relate to marks comment, do not ask any and an experienced quant a question about a statiscal formula…. But about how it could be used to solve or solution!. In the day and age of the internet finding a formula is not a problem… What is not prevalent and what distinguishes analytic talent is the ability to find the right use for the formula.
    The type of questions asked reflect the immaturity of the hiring employee..very unlikely that a quant resource is going to be happy in that environment.

    Reply
  4. Randy

    Solid article, but one point of contention on item #4. “Don’t hesitate to make an offer if you find what you’re looking for – your competitors won’t.” – Yes, they will, in my experience. That doesn’t mean you shouldn’t act swiftly when you identify a star candidate, but the sloth with which I have witnessed firms slogging through the interview & offer process is astounding. Getting through the process quickly, getting prompt feedback and timely offer will be a breath of fresh air if it ever happens again.

    Reply

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