About

For the formal resume, please see this PDF. For an informal overview, read below.

---

I’ve always had an active interest in the scientific method and basic science. Acting on it, I enrolled at the Texas A&M University in College Station, and pursued a degree in biochemistry. Through my undergrad, I tried to apply classroom theory in practice, working both as an analytical chemist (spectrophotometry) and a biochemistry technician (HPLC).

After graduating with a Biochemistry BS in 2010, I went to the Baylor College of Medicine in Houston, where I enrolled in the PhD program, also in Biochemistry. As I progressed with my studies, I became interested in programming and using computers to solve biological problems. I followed this interest and joined a computational biology lab, where I worked on evolutionary biology of RNA, and on graph learning via biological networks. Both of these projects are detailed on my home page. During this time I learned the basics of programming, statistics, and machine learning, as well as developed a taste for working with ambiguous, real-world data.

It took me a while to wrap up my studies at Baylor, and I graduated in 2019. Immediately following that, I did a summer internship as a Data Science Fellow at the Mercury Data Science consultancy in Houston. There I worked with real customer data doing A/B testing, customer segmentation, and churn modeling.

After my summer at Mercury, I took time off through the 2020 COVID pandemic. During the pandemic sabbatical I went into self-study and learned industry-standard languages and practices (eg I transitioned to Python from MATLAB, learned to work on the cloud and use version control, etc).

---

I am now looking to continue my professional journey, and searching for opportunities in the data space.