Watch our on-demand lecture on SVMs featuring Alice Zhao:  Get Recording 

Speaker Series: Aurelia Moser of Mozilla Foundation Speaks at Metis NYC

By Emily Wilson • February 01, 2016

Last week, we welcomed Aurelia Moser, Community Lead and Developer at The Mozilla Foundation, as our first in-class speaker of the winter Data Science Bootcamp in NYC. Our Chief Data Scientist, Debbie Berebichez, caught up with Moser before her in-class talk, to ask a few questions about her background, passions, and career. Read the full Q&A below.


Debbie: We are super excited here at Metis, New York, to welcome Aurelia Moser. Welcome.

Aurelia: Hello. Thank you.

Debbie: Your bio is super impressive. You have a degree in chemistry, but you wanted to do art preservation. Can you tell me a little bit about that?

Aurelia: Sure. There are lots of programs that groom chemists to be researchers and conservators for traditional art media, and I ended up going to grad school for that, deciding that I wanted to work with digital and net art and do preservation.

There are all kinds of problems with museums. They should have more acquisition programs based on digital art and net art, to preserve and make sure those projects are still live when their APIs are depreciated.

It was a really interesting problem to me, so I went to grad school for that. While there, I ended up doing a lot of coding to diagnose problems in digital art. After that, I ended up working at a tech company where I built my coding skills.

Then I started doing data visualization. And that was the closest thing I could get to art, but for the web. That turned into getting data science jobs and I ended up working with mapping. I did some stuff in humanitarian and resource research and now I work at Mozilla.

Debbie: That is fascinating. And you actually answered what was going to be my next question: how do you merge those two, at first seemingly distinct, professions of art and data science?

I would love our students to know that data science can be applied to art, and can be applied to a lot of other areas that we don't normally think about. What do you do at The Mozilla Foundation these days?

Aurelia: I work on the open science team, which is an independent research foundation doing outreach to scientific communities and scientists who want to use open data, or want to safely release all the things they're researching on platforms like GetHelp.

This includes the software they write, or we process their data and all the data that partners with their research projects. If they want to release those, we get them licenses and we support them through fellowships, and we also developed a few side projects that allow them to create study groups and build websites for their programs. So that's kind of what I work on now.

Debbie: Wow. That's great. I love Mozilla. I follow the foundation. I think our students are going to be delighted to hear about what you are doing. What is your message to young data scientists these days?

Aurelia: I guess just keep enthusiastic about learning different things. Because I think data science is one of those fields that changes so quickly and so often that you really have to be ready to constantly teach yourself. Even when you are out of school. Keeping hungry for that kind of learning is really important, I think, for success.

Debbie: That's wonderful. Thank you so much for joining us, and you're a great role model, especially for a lot of female data scientists out there. Thanks for what you're doing.

Aurelia: Thank you!

Similar Posts

data science interviews
Instructor Sergey Fogelson on the Importance of Grasping Machine Learning & AI Principles

By Emily Wilson • February 01, 2018

As Viacom's Vice President of Analytics and Measurement Sciences, Sergey Fogelson uses machine learning and artificial intelligence techniques almost every day. In this Q&A, he discusses why he's excited to share his knowledge with students in our upcoming Live Online Machine Learning & Artificial Intelligence Principles course.

data science interviews
Paul Trowbridge on the Importance of Having a Solid Stats Foundation

By Emily Wilson • January 05, 2018

Paul Trowbridge, instructor of our upcoming Live Online Statistical Foundations for Data Science & Machine Learning course, discussed the need for a firm stats foundation, talked about his career, and more during a recent Q&A.

Critical Thinking & Data Science: Conversations with Debbie Berebichez, Metis Chief Data Scientist

By Metis • April 01, 2019

As a physicist, TV host, and our Chief Data Scientist, Debbie Berebichez is always up to something interesting. Lately, she's been focused on the relationship between Critical Thinking and Data Science and discussed it on both the DataFramed podcast and the Story By Data YouTube channel. Check out both here.