I get it – you love digging into the data. The scientist in you loves being on the frontier of knowledge, and you’re always (at least feeling) like you’re on the verge of a breakthrough insight. The whole process of getting your hands on the raw data, the (non-always-so-fun) process of getting that data into a somewhat usable form, making your first hypotheses…the list goes on and on.
And let’s face it; this usually translates into long hours of high-intensity focus, where proper rest and recovery take a back seat (at best).
Pushed a Bit Too Hard
It’s a great feeling while you’re making progress, starting to see the underlying structure of the problem take shape; getting glimpses of what the final product and insights might look like. And there’s nothing wrong with putting in a substantial effort – after all, that’s what you’re paid for.
However, there is a limit – not just for what is reasonable for your boss/client to expect from you, but what you can expect from yourself.
For those of us who have not yet experienced professional burnout, it’s hard to cleanly explain what exactly it is or why it’s so bad. However, it’s becoming a major issue for data scientists: One study showed that over 25% of data scientists say they are ‘heavily stressed’
More than 25% of data scientists say they are heavily stressed
Basically, at least for me, it’s when you’ve pushed yourself too hard over a months-long process and you’ve noticed your motivation fall off a cliff. Your brain seems to have lost 20 IQ points and you can’t quite get yourself to care anymore about what you started in the first place.
You start feeling like you’re stuck in a fog, and the mini-breakthroughs that usually come so naturally (and frequently) start to become further and further in between. In other words, it’s a not fun position to be in, and it’s not always a quick fix to get out of it.
In my opinion, the old quote ‘an ounce of prevention is worth a pound of cure’ really comes into play here. Preventing burnout could be something as simple as minor tweaks to your work routine – while recovering from full-on burnout can take months, or even kick off a quarter- or mid-life crisis.
One way to think about burnout is like a stress fracture – repeated stress with insufficient time to allow the (individually benign) microfractures to properly heal up. We all like to think of ourselves as mental superhumans, but we each have a limit to how far we can push ourselves before our brain essentially shuts it down and demands time to ‘heal.’
For data scientists in particular, that implicit belief about being mentally stronger than average is a major risk factor for burnout – we think we’re invincible. That passion of finding the hidden relationships within the data, it’s so hard to turn off.
We are so busy solving awesome problems that we never really take time to consider whether we’re pushing ourselves too hard. And often, we don’t realize it until it’s too late – as in, a weekend trip isn’t going to be enough this time to recharge our batteries.
So what can we do to actually prevent and/or recover from burnout? Although I’m nowhere near an expert on the topic, from my (unfortunate) experience I have some thoughts on some things that at least worked for me.