I've been writing code to solve problems for about 15 years, mostly with Python but more recently with Scala and Java. I loving seeing the products, features, and fixes I've built go live and meet customer needs. My experience with Spark, Hive, and MapReduce make me comfortable working with data of any size. Overall, I specialize in building and maintaining ETL pipelines in Hadoop ecosystems, with a focus on tracking and improving data quality.

I enjoy tinkering with technology; digging into open-ended, data-driven questions; collaborating with awesome people; rooting for the Clippers, Steelers, and Mountaineers; board games; and traveling. I've also recently gotten into running, with one full & five half marathons and under my belt so far, plus more to come.

A few products I've built

commute-times

I got really tired of looking up four different commutes for every potential place we found on craigslist, so I built commute-times to do it for you.

You tell it where you and the people you'll be living with work, when each person needs to get to work, and when each person will be leaving, and commute-times uses Google Maps APIs to find where you can live that'll make everyone happy.

Currently only sports a CLI interface, but there's an extensive README to help you get started.

publist

publist is a set of python scripts that convert a list of publications from bibtex format (e.g., as exported from ADS) into both LaTeX & HTML formats, making it easy to keep both your website and your CV up-to-date.

sgklibs

While a lot of the code I wrote as an astrophysicist was tailor-made to produce a specific plot, sgklibs contains a variety of tools and libraries that help with common analyses and visualizations in computational astronomy.

leetcode_solutions

leetcode_solutions is —you guessed it—a collection of solutions to leetcode problems that I wrote up primarily in 2019. Most solutions include an explanation of how they work and of their time & space complexities.

basketball reference web scraper fork

Forked from @jaebradley's project, my version of basketball reference web scraper adds tools to get advanced stats, career stats, and playoff series from Basketball Reference. Most notably used in sheagk/nba_stats, where I experimenting with training ML models to identify first and second year NBA players who would become stars.