This is a draft chapter of a guide I’m writing to help people hired as the first “data person” in an organization. To make sure you don’t miss any new drafts or the release of the full guide, sign up to my mailing list.
A somewhat big disadvantage of being the first data hire is that you are likely to be the only “data person” for quite a while. Even when you aren’t alone, you will likely be the most senior hire for some time. This means you won’t be able to learn from peers or a more experienced technical lead or manager. You might be concerned you’ll be doing the same old things that you already know.
This is potentially one of the biggest drawbacks of being the first hire, especially if your technical skills are not yet where you want them to be.
It’s not a sure loss though. If you were surrounded by experienced colleagues, it doesn’t necessarily mean that:
- They would be good at coaching and mentoring or that you’d gel with them
- They’d have the time or inclination to help you
- They aren’t themselves stuck in their old ways
Being the only data person probably means you are at the coal-face of how the business operates. This is the single biggest advantage of being the only or most senior hire – there’s no filter happening above you. What a great chance to get to grip with all the stuff your managers and future managers really care about – the business stuff!
Here’s some ways that you can at least mitigate the lost opportunity to learn from someone more technically experienced than you in a direct-report kind of way. You may even be able to off-set this loss completely.
- In any projects that you outsource to consultants, build in a coaching component.
- For longer term projects, hire an advisory back-up to bounce ideas off of. I’m having great experience with this right now!
- If you get to hiring additional data-people, find someone with skills complimentary to your own. Are you able to throw a killer Tableau dashboard together but only kind-of get what a SQL CTE is? Then hire someone who does know and upskill each other.
- You can follow mentors from afar. All my best mentors have no idea they are mentoring me on all sorts of topics, technical and professional. I follow them on Twitter, read their blog posts, watch their screencasts, presentations and read their books. The best knowledge is out there and be willing to invest a couple of bucks here and there when necessary.
- Build in “learning time” to your project timelines and call it “project prep work”. Certainly easier said than done but this can be a good way to sneak in some learning.
- Make the case for Data Science as a team sport, but indeed your organisation can’t support a full team. Highlight where you need to grow to become fully rounded data professional.
- If you really can’t push for the things you want, latch onto the interests of your managers and rephrase in their language to get some skills in areas where you interests overlap with theirs. You may be surprised at the wonders rephrasing can do. Listen carefully.
- Yeah boss, we can probably do some AI. Can you give me a week or two to evaluate our options? (Cue high level crash course in Machine Learning)
- Yeah boss, automation could indeed save us money. Can I spend two weeks now to save us months of time in years ahead? (Cue automated reporting, scripting etc)
- Yeah boss, we could probably leverage X to do Y, but we’ll need database to do it. Let me do some investigation and get back to you with a way forward.
If your employer is hostile to learning, rephrase things such as “getting free advice/consulting, discounted workshopping”, and also start making plans to move elsewhere ;).
How much time is reasonable to spend on learning? I haven’t quite figured this out. I imagine it’s highly dependent on your own situation but I certainly feel guilty when I am “learning” how to do something before doing it. It’s mindset thing I am still working on breaking out of!
In my estimation, you’d be spending at least 4 hours a week speaking to a senior if one was around, so that is a good benchmark to aim for. Position it as that is what you’d be spending anyway. If you can set aside a dedicated half a day for this, say on a Friday morning, then you should hit a regular cadence of tackling subjects. I still need to experiment with this one and learn from others, so if you have feedback on what works for you, let me know!