I’m a data scientist in the Twin Cities. I got into data science through
chemical engineering, so, you know, the usual way. My research wasn’t very
conducive to data science, so I kind of made my own path. I co-founded
Penn Data Science Group, applied as many good coding
and data analysis practices as I could to my research, and ran a couple
tutorials/workshops to share useful tools (like Jupyter, Pandas, and Git) in
PDSG events and research lab meetings. I did a few side projects to pick up
skills outside of research. Here are some of the projects I had the most fun
- PBCluster: This is the only
one that actually had to do with my research. I put together a Python package
that I don’t think anyone but me will use, but I had fun doing it and learning
how to put together a tested, object-oriented, documented, pip-installable
package that helped at least 1 person (me) with their research.
- Collaborative Filtering Methods Comparison:
A detailed blog post comparing several collaborative filtering models for
movie recommendation with the MovieLens dataset.
- Citadel Data Open Championship:
My team’s report from the final round of a national datathon analyzing
- Interactive Baby Name Popularity Map:
An interactive map made with D3.js that lets you explore baby name popularity by time and
- NFL Fantasy Draft Dashboard:
A dashboard made with Plotly Dash just for fun to try to help with a 2018 NFL
fantasy draft. Turned out to be useless, but it was fun putting it together.
So many people helped me in my career development and job search process leading
up to landing an exciting data science job, so I’m always happy to (try to) pay
it forward with advice, encouragement, or connections. Please reach out to me
LinkedIn if you want to connect.