Why do companies struggle to recruit talented data people? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.

Why do companies struggle to recruit talented data people?

I can think of a few reasons. There are certainly more, but these are a few I hear all the time:

  1. They don't know what they want. Quora's own Head of Data Science, Eric Mayefsky, wrote a killer answer that approaches this from the opposite angle -- tips for writing a Data Science resume when coming from academia. In his answer, he recommends candidates be really thoughtful about the type of role they are looking for; what flavor of Data Science they want to practice. I believe this is necessary for companies as well. If you're writing up a job req, make it clear what goals the person is being hired to meet and what resources are available to help meet them.
  2. They don't have hard data problems. This is really a more specific (and, frankly, very common) extension of the previous point. There are plenty of folks out there who want to work with the latest technology or solve problems in really complex ways. The reality is that most jobs don't require that, and someone who wants to solve problems in unnecessarily complicated ways could be counterproductive. Unfortunately, companies can't really solve for this -- the best they can do is weed these folks out early with detailed job reqs and careful screening.
  3. They don't actually know how to evaluate them. Companies tend to use technical skills to screen people out early in their recruiting processes. I think a lot of them recognize that communication and problem-solving skills are what make for really great teammates, but nobody seems to know how to screen for those things, so they end up with a flood of candidates with deep technical knowledge and few other skills. I wrote a whole blog about this specific challenge.
  4. They don't value or understand the practice. And some simply don't care. This manifests in lots of ways that great candidates can sniff out quickly. Who does the role report to? Does that person think about Analytics or Data Science as invaluable? How do they see the data team contributing to the company as a whole? As an example, I very rarely see Analytics thrive when it reports through Finance (Intercom is the notable exception) -- really talented analysts don't want to be dashboard monkeys, and they will turn and run if they sense that their manager thinks of the role this way.There are other signals here as well. How much budget is allocated to the team? Can they buy the tools that they will need to be really successful? Can they hire supporting roles like data engineers or product managers? Basically anything that communicates the notion of "we just want it to work" will send talented folks out the door and on to the many other places looking to hire them.

The amount of effort required to get around these isn't super high, which leads me to believe that, for companies that really struggle, the real problem is #4.

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