At Atlas AI, we believe that in order to achieve our mission of improving lives in the most vulnerable parts of the world, we need to build a diverse team. We’re thrilled to have five women to date on our data engineering team who are driving our innovation and projects forward. To celebrate them and in hopes of inspiring other women in this field, we are sharing a little bit of their story with you.
Introducing Emily Logan
Emily worked as a Water Resources Engineer focused on driving data driven decisions related to water management, through the use of dashboards and visualizations. She has experience managing large, collaborative projects and stakeholders, and managed the efficient use of all water rights for the City of Pueblo in Colorado. She also worked on analyses and designs related to water distribution systems and water consumption. She has a Bachelor’s in Statistics from the University of Chicago and Master’s in Environmental Engineering from Northwestern University.
Emily joined Atlas AI three months ago as a Spatial Data Science Project Manager to contribute to the commercial side of the Applied Data Science (ADS) team, which involves helping with analysis depending on the clients’ needs. The other half of her function involves project management and coordination for the Rockefeller Foundation project over the next 3 years.
Did you have a role model that influenced your decision to work in Data Engineering?
My sister has been my biggest role model and I often followed in her footsteps, to some extent. I’ve always enjoyed math and sciences growing up, but I had trouble picking my favorite between the various topics. My sister was the first to really show me the applications of statistics in high school and it was the reason I picked that major in college.
How and why did you choose to become a Data Engineer? How and why did you choose your field of study
I’ve always enjoyed math and science, but really had trouble picking a major in college. I wanted to make an impact on the world in many different aspects - from social to environmental - and wasn’t sure which path to take. Statistics was a way for me to combine the subjects I enjoy while applying my studies to real world problems. I minored in environmental studies in college, which led me to my masters in Environmental Engineering. I worked in many arenas of civil and environmental engineering before joining Atlas AI and getting back into the data science realm.
What is your proudest achievement in your career thus far as a Data Engineer?
Since I’m relatively new to data science, it’s working here at Atlas AI. But before this as a Water Resources Engineer, my proudest accomplishment was driving data driven decisions at Pueblo Water. I showed them the power of geospatial dashboards and making decisions using the extensive data they had. I wrote their first water efficiency plan and implemented a $1M cost share with the parks department to use technology to conserve water.
Which topic do you think should have more Data Engineering attention?
I think water operations could use more of a data science approach. There is so much data generated from water utilities and they don’t do much with it or only put it into operational models. I think if you could use statistical principles and model development, it could work better with changing dynamics of water use.
How did you persevere in a men dominated field?
I tried to connect with the women around me; joining organizations like Her2O if there weren’t any or many women around.
What were the biggest obstacles you had to overcome because you are a woman?
Gaining respect from peers and colleagues. In civil / water engineering, I would see my male counterparts have more opportunities for client interactions than I did and it was really frustrating. I used to be much more reserved in a group and because I needed to make my voice heard, I really had to overcome that in order for people to respect my opinions.
What kind of prejudices did you have to face? How did you overcome them?
I had contractors not respect me because I’m a woman and even colleagues imply I only got positions because of my gender. I think overall, the prejudices were always centered around my intelligence, that a woman couldn’t possibly be as smart as a man, and that always drove me to learn more. Luckily, I have never faced prejudices from a close colleague or manager, which helped me gain confidence in my work. However, I think that speaks a lot to the nature of these comments - they never came from someone that directly knew my work - and for new women engineers, it’s important to keep those negative voices out of your head and keep learning.. The voices that matter will respect you and the hard work you do.
Which changes are needed in the Data Engineering system to be more inviting to women to JOIN and STAY in science?
There needs to be more women in leadership positions to change the culture.
What is your best piece of advice to women interested in / already in Data Engineering?
It’s a great field with a lot of different applications and we need more women! Have confidence in the work you do and your training!
What do you hope to see in the future in Data Engineering?
More women in leadership positions.