I started my career in geology back in Las Vegas, when I went back to school to study earth sciences after a career in human resources. I really loved the rock aspects of it, so I transferred to the University of Boulder in Colorado and got a Bachelor’s degree in geology. It was there that I developed a real interest in subsurface fluids and pressures and began developing my coding skills. I got into 3D printing working in the Mathematics department, where I built manipulatives for the calculus series—physical objects that students use to learn about calculus, which required some coding.
I then pursued a Master’s degree in petroleum geoscience at Imperial College London. My thesis focused on using deep-learning neural networks to address issues in the North Sea around subsurface pressure and compartmentalisation of reservoirs.
After graduation, I saw the job advert for a data geoscientist at Data Hub. It seemed perfect because it combined data aspects like coding, which I was getting into, and the geology background I already had. I’ve been with Data Hub now for about 14 months.
A day in my life starts with coffee. Lots of coffee. My team has a check-in meeting to unpack what we’re tackling that week. Then, it’s on to planning and writing scripts before turning to data extraction.
Knowing what to extract requires some geology knowledge, but my background really comes in during QC—understanding the data, where it will live in the database and how it will be used.
My first Data Hub project in Brazil combined traditional reservoir geology, seismic interpretation and reservoir engineering data extraction. The geologists wanted to interpret the horizons and faults in the subsurface. I met so many people on the team through this project, which was fun.
Data Hub really lets you play to your strengths. I am a data scientist and geologist, but I’m also quite creative and like to interact with people, which is where my side projects come in. I designed the hoodies for Data Hub, which all the team wears. I also make project badges, like NASA does, that team members can collect, stick on their laptops, put on profiles or use in slides. They’re great conversation starters.
My first real experience was at university. The pandemic hit while I was studying at Imperial, so there wasn’t a lot of in-person interaction. Instead, we formed a group chat of all the women in the course so we could discuss course issues.
My experience with the global WiDS community has been great. There are regional workshops and Datathon challenges that tackle different issues and encourage collaboration.
It fosters an atmosphere of inclusion and learning in a field where women are underrepresented. This helps show younger girls what’s possible and also helps women already in the field feel like they belong, breaking down any imposter syndrome.
I have a lot of hobbies that keep me busy. I’m originally from San Diego, California, and I enjoy most outdoor pursuits, including skateboarding, surfing and hiking. I’m also a keen bodybuilder, often waking up at 4 a.m. for weightlifting. Finally, I also do aerial acrobatics with fabric silks, training after work at local classes and even the park.
I’d love to develop more machine learning expertise. The artificial intelligence and ML aspects of data really fascinate me. I’d also love the opportunity to continue to share my knowledge with others, going into the community and speaking to young women about this career pathway.
