How To Hire Analytics Talent

I went on an interview recently and spent a bunch of time discussing what the potential hiring company’s biggest pain points were.  They were in the web commerce space and expanding very quickly.  The biggest theme was around growing pains.  Specifically, how to maintain the company’s successful culture, avoid redundant work (ie two people on different teams doing the same project without knowing about the other) and hire, especially for middle management.  This got me thinking about two things.  How difficult it can be to scope out projects and how to hire people for analytics work.

I am constantly surprised by how difficult it is to predict project timelines, especially early on before getting my hands on the data.  One of the ways that middle managers in analytics can provide value is by being a middle person between the technical folks doing the work and the end users and business sponsor (the person whose budget this is hitting) to help improve these projections.  Having experience building analytics tools (especially if they’re going into a production environment) makes a huge difference in the quality of timeline projections, the ability to source needed talent and explain processes to non-technical folks.

Frequently, technical folks don’t interact well with business folks as the business folks want their problem solved while the technical folks are in the weeds on technical issues without actually understanding why they’re doing it in the first place.  Often, I’ll see too big of a gap in role and seniority that leads to senior business folks making demands of junior technical folks who are too inexperienced to push back or ask for more information before large amounts of time and resources are expended in the wrong direction.

As far as hiring, things I look for are as follows:

  • Don’t be a jerk
  • Do be detail oriented – ask lots of questions
    1. How many rows of data do we have?
    2. Does this make sense?
    3. Which rows can’t we use? Why?
    4. Is this data timestamped?!?
  • Be good at manipulating data (SQL & Excel !!)
  • Understand some stats (ie how can I tell if a variable is important in a regression model?)

Obviously, there are many other layers but these are pretty good to start with.  Another easy filter (I’ve only had to use once) – don’t ask the admin for a selfie with the company logo…

 

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