I Am Data Science | Shannon Ellis

HDSI Feature Faculty Series: I Am Data Science 

with Assistant Teaching Professor, Shannon Ellis, Ph.D.

by Trista Sobeck & Bobby Gordon

Shannon Ellis is an Assistant Teaching Professor in Cognitive Science and the Halıcıoğlu Data Science Institute at UC San Diego. She earned her Ph.D. in Human Genetics from Johns Hopkins School of Medicine. Her primary focus at UC San Diego is to foster and promote data science education. To this end, she teaches undergraduate Programming and Data Science courses. She pursues projects that help provide access and educational materials to individuals who have historically lacked access to data science education.

Shannon Ellis, Ph.D., who spends much of her time with students trying to break into the data science field, has a short and sweet working definition of data science that she uses in class. Recognizing it does not even attempt to get at all the nuance that the term carries, she uses “the scientific process of extracting value from data.”

Ellis makes it clear that sometimes value does have a monetary meaning, but often the value comes from the inherent insight or knowledge that data brings.

Ellis’s field of research is in human genetics. Even before data science emerged as an actual field of study, she was working in it. “I was collecting and analyzing large genomic datasets and using programming and statistics to do so,” she explains. These are the skills that are expressly what most data scientists do. At the time, the emerging field did not even have a name.

Early Experiences in Data Science

“[The field of] data science felt like a natural fit,” says Ellis. “I certainly wasn’t a computer scientist – but I wrote code every day. I was not a trained statistician – although I regularly used statistics to answer my questions of interest,” she says.

She seamlessly ended up in data science and then later data science education. Because Ellis was at the forefront of the field and was essentially teaching herself the rudimentary ‘tasks’ of what a data scientist technically does, the field of education felt like a very natural fit.

There are as many entry points into the field of data science as there are data scientists. “While I entered the field through human genetics, most of the research I now do is education-focused and carried out with the help of some amazing undergraduate students,” explains Ellis.

“I am now focused on understanding what, how, and why my students learn, with the ultimate goal to improve our understanding of data science education.” She adds that her aim is a tad selfish as she always wants to “improve how she teaches.”

From a publication standpoint, Ellis, UC San Diego professor Brad Voytek (HDSI & Cognitive Science), and instructor Tom Donoghue (Cognitive Science) recently wrote about her pedagogical goals in teaching COGS 108, Data Science in Practice. Because of her background, Ellis knows first-hand what it means to use data science to solve a problem or gain insight – as she was doing so when data science didn’t even formally exist.

Also, she continuously collaborates with others to help analyze biological data and recently submitted two papers from working with UC San Diego Professor of Clinical Pathology and Director of Toxicology, Rob Fitzgerald. Ellis’s background in biology and science always seems to be helpful.

Ellis is driven by helping people. She says she gets most excited when she thinks about applying data that helps individuals, marginalized groups, and society in general.

Using Data Science to Make a Change

“Unfortunately, and possibly at a faster rate, we also see how data can be used to harm individuals, punish groups, manipulate people, and grow societal inequities,” she observes. “So, I’m hopeful that the field will increase how much it prioritizes and listens to the experts in the field of AI/DS ethics. Furthermore, I’m most excited to see the continued development in the application of data science for social good,” she explains.

Words of wisdom to a future data scientist? “It is a competitive but rewarding field,” Ellis says. “Data scientists have the opportunity to constantly learn new things throughout their careers while asking and answering really interesting questions…which is awesome!” she explains.

“However, given how hard it can be to break into the field, I like to remind people (particularly my students) that nobody knows everything there is to know about data science, even if they act as they do,” says Ellis. “So, think about the role you want and then build your skills and knowledge toward that goal. Build your portfolio (independent projects, internships, etc.) so that it appeals to the people in the field/at the company where you’d ultimately most like to work,” she explains.

From a skills standpoint, Ellis, inspired by Vicki Boykis , gives six salient suggestions for data science students to embrace for their education and careers:

1) Learn SQL

2) Learn a programming language/programming concepts extremely well

3) Learn how to work in the cloud

4) Learn statistics/statistical concepts

5) Learn how to communicate effectively orally and in written form

6) Be willing to learn more constantly

From there, you will be on your way. Moreover, as in Shannon Ellis’ case, don’t be afraid to try to make a difference in the world. Through data, insight, and a little problem solving, anything is possible.

Connect with Dr. Shannon Ellis

Twitter: https://twitter.com/Shannon_E_Ellis

LinkedIn: https://www.linkedin.com/in/shannon0ellis/

GitHub: https://github.com/ShanEllis

Personal website: http://www.shanellis.com/

UC San Diego/HDSI Faculty Profile: https://datascience.ucsd.edu/about/faculty/faculty/name/shannon-ellis/