Biggest Challenges Faced By A Data Linguistic Analyst At Meta

My role has easy parts and hard parts. The hard parts are sometimes the resilience that's needed to challenge a language model for the better portion of a whole day. That can be really difficult over a long period of time.

I definitely have to prioritize my rest or make sure I've taken care of myself in order to do a good day's work. Otherwise, staring at a screen the whole day can be pretty tough on anybody.

I think that's an important part that I'm learning now. My days are actually kind of longer than a normal school day, where you have lecture and homework, and it's not always on a screen. Coming up with new ideas can also be really tricky.

Sometimes you are in a more conducive environment mentally, or sometimes you have other things on your mind. It's tough, and maybe those other things going on in life can distract you with your work. So, it's kind of a give and take there.

I personally find it challenging sometimes to be so isolated in my own work. It would be nice to have a bit more camaraderie and teamwork on the specific task I'm working on that day.

Another thing that's challenging more personally is sometimes the barriers between my laterally and vertically. I often don't have any knowledge of what's going on on different teams that are adjacent to mine. It might be relevant for the overall project, but I don't necessarily need to know.

Also, in terms of my boss's boss, it's very difficult to have any idea what their work is like because they're super busy and dealing with tons of people. I appreciate transparency a lot, and that's something that sometimes I find challenging, but it's also comfortable just being in my own space.