2024, a reflection
For this year’s reflection, I thought I’d switch things up a bit.
My Wins in 2024
I got my first role post-grad doing work that was completely different than what I earned my master’s degree in.
Now you may be thinking, “How is that a win?!” But hear me out.
Many of us have faced the prospect of taking on a role other than what we studied in school, and this can be majorly disappointing. It was for me, especially towards the end of my first degree, when a mentor sat me down and explained to me that many biology majors don’t have great job prospects outside of a few directed paths. By that point I already had vestiges of a plan of what I wanted to do next, I just needed the platform. I had to seriously consider what my next steps would be.
Fast-forward to 2023, and I was the fortunate holder of a masters diploma in Biostatistics. I had already done some related work while I was in grad school giving me great exposure, however funding ran out for my position, leading me to look elsewhere for work. Up until that moment, I had completely underestimated the job market for Biostatisticians that year. Many positions were looking for mid-level, senior level, and even director level roles. In the spirit of trying, I applied to all of them despite having less than a year of experience. Unsurprisingly, I received no callbacks.
I was reticent to broaden my horizons, mostly because I felt very strongly that if I went to school for a degree, I should be able to find a job with the same title as the degree, especially with a masters in a medical science. It felt like a completely fair line of thinking.
However, life isn’t exactly fair.
So I failed and I failed until I widened my search a bit. I started to applying for jobs with data analyst, clinical analyst, etc. in the title. Much to my surprise, this worked, and I got more callbacks than my previous efforts. I eventually landed a job as a data analyst at a large health insurer which I was pretty excited about.
I don’t know what I expected when I applied, but whatever it was, it was completely different from what I actually ended up doing in my day-to-day. A lot of my work involves constantly accessing databases which in hindsight should’ve been obvious, however it wasn’t from the outside looking in. You see, in my program there was no focus on databases, and at most I had a bit of PROC SQL experience due to my own exploring of SAS software. This wasn’t unique to my program either, as I’ve found that other masters programs in biostatistics did not have a database course or curriculum component. So I was at a bit of a disadvantage. However, I was very fortunate in that my job trained me on how to use it.
What’s interesting is that I don’t use any statistics in my role. Instead, I spend my time thinking about how data is stored, where it is stored, protecting it, optimizing queries, etc. These are all things I never gave much thought to as a student. Each data point I encounter represents a constellation of brand new topics to cover.
It’s funny because as a masters student, I was simply provided cleaned and processed datasets to practice with for my work. I remember I did a research project where I sought out data, but even then those datasets were pretty clean. And, a lot of companies or other organizations are not amenable to providing unclean proprietary data for students, so you kind of just are stuck with these very sanitized resources. You’re not really storing them on a database or anything like that, so all you have to do is point your IDE wherever they are stored to do your analysis.
In this role, all of that goes out the window. I’m constantly juggling different priorities, because how this information is managed can have very real effects on people’s lives. My work intersects with so many different fields, and it’s quite exhilarating to see how they all coalesce to positively impact people’s well-being.
Since I started this role, I’ve been empowered to go out and learn more about databases to up my skill set. I took a MySQL course at my local community college recently, and have taken that knowledge and have tried experimenting with creating and managing databases for personal projects on my own time.
This new perspective also reshapes how I view my previous work as a statistics student. Effective data storage is every bit as crucial as the conclusions you draw from the data itself. In fact, proper data storage might be even more important—store data incorrectly, and you can hinder or even derail the entire process of downstream analysis.
So, what am I trying to say with all this yapping?
Keep an open mind, you never know what you might learn.
What I hope to gain or continue in 2025
I hope to continue increasing my knowledge base. I think my main goal right now is to continue deepening my knowledge of current tools and exploring new ones.