Range vs. Expertise
My take? Have Range but be Goldlike in at least one thing.
If you’ve worked in Tech for a while, at some point, you would’ve come across two opposing thoughts. ‘Range’ vs. ‘Expertise’. Be a ‘Generalist’ or a ‘Specialist’. And I’ve had moments of reflection on this over the years.
Literally nobody actually gives a shit about this. It’s just one of those things people talk about because they want to put you in a box. People who prefer ‘Range’ will tell you that knowing a bunch of different things helps. It helps you understand other perspectives, job functions, etc. I would personally put myself under the group of ‘Range’ for sure. The ‘Expertise’ group seems to be on the other end. Think of a statement like ‘being average at everything doesn’t mean much’.
There’s truth to both statements. At least, that’s what I think after 10 years of working. Let me give you a few examples.
As a Data Scientist, my role requires me to know the following:
Programming/Tools: Excel, Python, R, SQL
Math/Stats: Statistics, Machine Learning
Collaboration: Ability to work with PM, Designer, Engineer, Marketer, and Leaders
Communication: Ability to draw insights and communicate them effectively
Learn: Keep up with the market and where it’s going in terms of tech
If you’re only good at, let’s say, Programming and Learning, it would mean that you’re Godlike at these things. You’re constantly in the deep end of what’s happening within the Python community and can basically do anything new that comes out. And you would surely be quite successful. That’s great! If you are that, then you should do that and be the ‘Expert’ that you are.
Some people want to be good Programmers but also have top knowledge in the Statistics department. They are Godlike at Statistics, quite average at Programming, but can get the job done. And that’s fine too. At least, they’re the go-to person for Statistics and have enough skills in other departments to keep going.
But that might not be possible for everyone. Or that it might even interest everyone. And that’s totally fine.
Some people are great at some of the other skills mentioned above, and probably are average at Programming and Statistics. The good news? There are jobs where they can fit right in.
Every Data Scientist has seen JDs filled with 10 different tools, 3 programming languages, all the statistics in the world and don’t even get me started with the Machine Learning bit. Truth is, very few jobs need you to be an expert at all those things. What matters most is to be Godlike at one of those skills and have decent competency in the others. Range, but with specialising in one thing, so you become the go-to resource for that skill.
I’m learning this the hard way today. And hope to do so again when I’m hit with a wall. Be a specialist at what you’re already good at and keep pushing the boundary for what more you can learn in it. But at the same time, make sure to stay competent in the others.