About Me

Hi, I’m Sonia — a junior at Baruch College studying Mathematics.

A lot of the work I’ve ended up doing comes back to a pretty simple question: what’s actually going on here? Sometimes that means testing whether a model is really working, digging through a messy dataset to explain an unexpected result, or realizing that a metric or assumption doesn’t quite tell the whole story.

More and more, the way I answer that question is through statistics. I’m especially drawn to the investigative side of the work: following strange patterns, tracing them back to their source, and deciding what they actually mean, including whether the measures we rely on are capturing what we think they are. On a school-absenteeism project, for example, I found an undocumented shift in a city data index that had quietly affected models trained across the change. That project stuck with me because the interesting part wasn’t simply building a model — it was discovering something about the data that changed how the results should be understood.

I also care a lot about what happens after you find something. Ideally, technical work should help someone make a better decision, see a problem more clearly, or build something that works better for the people using it. That’s part of why I keep ending up near policy, education, and AI governance: technical questions and human decisions are rarely as separate as they look.

Where I want to go from here is a research career in applied statistics, starting with a PhD. What excites me is using statistical methods to find things out — whether that’s a new metric, a better way of measuring something, or just a careful answer to a question that hasn’t gotten one yet — across whatever fields have interesting data and real decisions riding on it. The short version: investigate interesting problems, understand what I find, and make that understanding useful.

That interdisciplinary instinct isn’t exactly new. My path here has involved math, statistics, and machine learning, but also student government, committee work, teaching, and questions about how universities are navigating AI. I’ve worked as a design consultant for a new first-year AI literacy course at Baruch and served on the university’s AI Leadership Initiative Core Team. I like having one foot in the technical side of a problem and another in the people and institutions that actually have to deal with it.

A few unserious facts about me:

• My lucky charm is a smiley face named Bob that I draw on every exam.
• Sharks are my favorite animal — hence the GitHub profile picture.
• I love em-dashes and will never stop using them, regardless of their association with AI-generated writing.

Check out my CV for the more formal version of what I do, and my GitHub for things I’ve actually built. I’m working on making the latter easier to explore and try.

And if you want to talk about statistics, data science, research, policy, or whatever you’re currently working on, find me on LinkedIn. I genuinely like hearing what other people are figuring out.