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how to apply it to biological problems. I did a lot of work using random forest
for research in comparative genomics.
I loved the internship so much that I knew I wanted to do something with
statistics and biology after undergrad. I started the master's program in
biostatistics at the University of Michigan and later went on to do a PhD in
bioinformatics, also at Michigan. When I finished, I decided that the traditional
academic path wasn't for me, and I wanted to work on challenging problems
in data science. Interestingly, even though academia was ahead of industry in
applying the techniques of machine learning, it lags in the effective use of data
technology. I thought that to really learn that technology, I needed to leave
academia, and that's what I did.
Gutierrez:
What advice do you have for current undergrads?
Shellman:
My advice to undergrads is to study computer science, math, or
statistics, and a combination of the three. It doesn't matter what else you study
alongside them, if you have those three skills, you can do whatever you want,
literally. I think the opportunities are endless, which means you don't actually
have to commit to any industry. I can't advocate enough for the study of math
in general and the maths more broadly because it's where you learn to reason
and think critically. The really exciting industries that are experiencing a lot of
growth all involve math, computer science, and statistics in some way.
Gutierrez:
Now that you are in the industry, what are you studying?
Shellman:
Right now I'm studying programming and computer science, and
I'm hitting it hard. I'm going to a lot of meet-ups, speaking at a lot of meet-ups,
and even organizing one. I'm a co-organizer of the Seattle chapter of PyLadies,
which is an international mentorship group whose goal is to help women
become active participants and leaders in the Python open-source community.
I'm also revisiting some old projects from grad school and applying my new
and improved data skills to see if I can revitalize them.
I'm at a point where I feel myself getting up this mental hill. I'm done learning
basics and have a good sense for how all the pieces fit together and I'm build-
ing on that knowledge. Although I'm starting to realize I've gotten hazy on
things I was solid on before, so I have to go back and review. I have to make
sure I am maintaining a balance between programming and math.
Gutierrez:
When did you realize you wanted to work with data as a career?
Shellman:
I knew I wanted to go into science as a career after my internship
at the NIH, and collecting and analyzing data is a huge part of scientific work.
I don't think I was ever really aware of wanting to work with data
per se
, I just
wanted to answer cool questions. Data's just the world making noises at you.
I think I was more interested in the application first.
