Reality of an average college student trying to start their career

What’s going on, everyone? I guess this is going to be my first proper post. I want to talk about two main topics: building a career and figuring out what you actually want to do with your life. They’re connected, obviously, but they require different approaches.

The stress behind starting out.

I think most people reading this will agree: being in college is nerve-wracking. You see everyone doing a million different things, and it feels like a race where you’re stuck at the starting line while everyone else is sprinting ahead.

I felt the exact same way. I saw peers already landing internships and jobs before their freshman year even ended, and it was terrifying. In my experience, that gap is intimidating, but you can close it through consistency.

For example, a friend of mine landed a semiconductor internship immediately after our first year. Looking back, he’ll tell you it wasn’t the most prestigious role in the world—but it was a start. At the time, it terrified me. How did he land something so fast? Am I already behind? He worked through the summer while I was honestly, doing a whole lot of nothing. Just hanging out and partying.

But watching him land that job was I guess motivation in a sense I spent some time making my first proper resume. Spoiler: it was hot ass. I didn’t receive a single callback, coding assessment, or interview. By the second semester of my sophomore year, I was panicking that I had nothing lined up for the summer. But around that time, I met some people who told me about undergraduate research, which led me down the first rabbit hole of my career.

The mess that is academia.

Once I learned what undergrad research actually was, I decided to “spray and pray”—I spammed my resume to every lab at my school. For context, all I had on my resume was a fast-food gig, a call center job, and a random class project. Nothing to write home about.

After sending applications to a couple dozen labs, a grand total of four hit me back: three psychology labs and a cosmology lab. Not at all what I was expecting. The psychology labs wanted to know if I had any psych background. I told them, “No, but I can code and do data analysis.” They were not fans. We can call those insta-rejections.

The cosmology guy was a bit of an odd ball. He just said, “Hey, we’re having a meeting today. Show up, sit there, and we’ll talk after.” I showed up about 20 minutes late because he sent the email the same time the meeting started. I sat there and understood absolutely nothing. Afterward, he told me: “Just keep showing up. If you hear about a cool project, go ask that person if you can help.”

(Side note: None of my other research experiences have been this casual. This was definitely an outlier.)

I sat in those meetings with nothing to do for a month and a half. Finally, a grad student mentioned he needed help identifying caustic transients (I’ll explain those in a later post). It turned out to be mostly data labeling. I’ll be honest: for academics doing “cutting-edge” astrophysics research, there is a surprising amount of manual scanning—just looking at images with your own eyes to find sources.

I used to think of academics as archaic for not automating everything, which was judgmental of me, but the experience was great. It gave me something technical to talk about on my resume. The point of all this “yapping” is that when you’re starting out, any experience matters. Even if it’s in an unrelated field, it’s still technical experience you can use to bridge the gap in interviews.

Figuring out what it is you want to do with your career.

Participating in that research (and another lab later) for over a year helped me realize what I was actually interested in. I found my niche at the intersection of Data Engineering, Statistics. Once you find that focus, things actually get easier.

For me, focusing on the Data Engineering side made building projects way more fun. I didn’t feel pressured to build a flashy ML model; I just focused on extracting, transforming, and loading (ETL) data from different sources and creating dashboards. Projects don’t have to be complex—they just need a clear use case that you can explain simply on your resume and in interviews.

For next time.

Tbh I’m kind of done yapping for now but I’ll have a continuation of this focusing on my experience with math research and how impactful the experience was. As well as talking about some projects both personal and for school.