If You Quit Now, They Will Be Right

I saved that image to my phone a few months ago and I keep going back to it. Spike Spiegel leaning back with a cigarette, looking like he’s given up on everything except whatever he’s about to do next. It’s a quote that has been reassuring for me the past couple months, or a least a reminder of the path forward.

I’m 25, and I live at home with my parents in the suburbs. I work at a pharma company where I build BI dashboards and write SQL, and it’s fine. I’m grateful for the job I have, and I do have a great support system with amazing friends and a loving family. I try to stay grounded in that. However, I do dream bigger than writing SQL queries for a dashboard that no one truly cares about. Despite that, I’ve learned that the monotonous is important, and quite valuable in the long-run. That day-to-day grind gives a lot more than you realize in the moment, and I’ve been trying to maximize the growth and learning I have at this stage by committing to the work despite it being a slog at times.

This was a lesson I had to learn the hard way. Somewhere along the lines of eight years of competitive running, I lost sight of the fact that dreams and aspirations are the easy part. As I got near the end of my career, I forgot the 5 am wake-ups that I had in high school, and the thousands of miles that I racked up in the summers were what helped set me up to run well, not the singular workout in February. At some point, I forgot about the foundations and didn’t give it enough care. This time around however, I’m cognizant of that, and I try to make sure I’m maximizing what I can every day even if it is tedious at times.

I’ve been applying to data engineering and ML engineering roles for a while now. I don’t know the exact number of applications anymore because at some point counting them stopped being useful information and started just being depressing. What I can tell you is that I have gotten very good at reading the phrase “we’ve decided to move forward with other candidates” without feeling anything.

The rejection thing is weird because it’s not like any single one of them hurts. It’s more like, you apply, you wait, you get the email or you just never hear back, and then you do it again. And again. And at some point you start wondering if maybe the problem is you, if maybe the resume is wrong or the projects aren’t good enough or you’re just not what companies are looking for right now. And I don’t have a good answer to that. I genuinely don’t know. Maybe it is me.

But I’m not going to quit

I think about the George Box quote a lot. “All models are wrong, but some are useful.” It’s one of my favorite quotes, and has been since I first heard in Greg Matthews class at Loyola (s/o Greg). The thing that quote really reinforces for me is that people get so caught up looking for the one ground truth, the one right way to do something. But no model explains a random variable right 100% of the time. There is no crystal ball. You’re never going to perfectly predict what happens next, no matter how many features you throw in or how fancy your regression gets. That’s not the point though. The point is that some models explain the variance better than others. Some give you a better sense of what actually impacts what, especially when you’re dealing with complex variables and a ton of noise. And that applies to life just as much as it applies to a stats problem. There’s no one path that’s guaranteed to work. Nobody’s got a perfect read on which decisions lead where. But some approaches are better models than others, and I know what I want long term. I want to build ML systems and work on problems that actually matter to people. I don’t want to spend the rest of my life building stuff for people who couldn’t care less about the actual product. I don’t have a crystal ball for whether this specific combination of grad school classes, late night projects, and job applications is going to get me there. But it’s a better model than sitting still and hoping something changes on its own.

The reason I keep coming back to that Spike image is that the spite is real. However, it’s not directed at anybody. It’s more like, every time an application goes to trash, every time the scale doesn’t move, it all just accumulates into this thing where I think, okay, if I stop now then this is the final version. This is where the story ends. This is what my effort and ability have lead to. And I’m far too prideful for that. I just don’t want the rejections to be the last thing that happened.

So I’m not going to quit. Not because I’m confident it’ll work out, because honestly I’m not. I’m just not ready to let the rejections be the final word on whether I was good enough. That alone is enough to get me out of bed and in front of the laptop after a ten hour day.