A Data Hiree's Bill of Rights
This morning, I was talking with a friend of mine collecting thoughts about the hiring process and subsequent work environments for data scientists. She had identified the problem I hear about so often through my work: companies need data people but the hiring process is as flawed as the lack of efforts to retain such talent. How do we make our organizations cultivate an environment where data scientists can thrive with their unique set of skills? Shifting organizational culture may not happen in a day. So with that in mind, I made a short list of things that YOU as a data scientist can do to advocate for yourself in the meantime - a data hiree’s Bill of Rights:
I'm Your Scientist, Not Your Sensei
And if you’re going to tack “Sensei” onto my role, I expect to be compensated. Many data scientists hired onto teams complain that their managers have no sense of data literacy and expect the data scientist to educate the team in addition to all other data processing responsibilities. If as a manager, you feel that your team needs both a data scientist and a coach on data literacy, either make that clear to your candidates in the interview and ensure compensation for whatever teaching will be involved, or bring in a third-party data literacy coach to debrief the team. I have a feeling these coaches will appear more and more on the scene in coming years.
If You Call Me, Be Ready
What do data scientists and uber drivers have in common? We’re often called before the person who needs our services is actually up and ready. I get it, managers. Your dollars and the direction in which they go are sacred. But if you bring me on to determine using my data skills where your dollars should be going, be prepared to listen and shift your focus accordingly. Often, the pain points you’ve identified based on intuition will not match what a data scientist can pull from your metrics. That is why so many managers will defensively argue with the data scientists they’ve hired or worse, ask these people to lie. Change is scary and there’s always an adjustment curve. But make sure the company you sign onto is ready to hear and follow your advice. If not, they’ve wasted your time and theirs.
Psst…Over Here!
Some managers still insist that there is a lack of diverse talent in data science. That couldn’t be further from the truth. Yes, we probably don’t feel comfortable enough yet with the industry’s culture to be in your exclusive room so you won’t see us there. That doesn’t mean we’re not out there. So where are we? I see a lot of you asking. And the truth is: We are on social media! The data science community on Twitter is vibrant and strong, not to mention full of self-taught data scientists from diverse backgrounds claiming our space. Managers, make sure that your head-hunters are scouring social media thoroughly in addition to pooling their existing networks.
This post is just scratching the surface of the things you can do to assert your power as a data scientist in any workspace. If any of you are interested in how such techniques can be applied to your personal situations, please remember that I am available for 1-on-1 consulting sessions!