Jamie Montgomery, MESM 2013

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When Jamie Montgomery graduated from the Master of Environmental Science and Management program in 2013, she knew that she wanted to combine her long-standing interest in marine science with the coding and data analysis skills she had learned at Bren. There wasn’t yet a standardized name for the job she envisioned, but she found it in her role as a marine data scientist with the National Center for Ecological Analysis & Synthesis (NCEAS) that combined her interests.

Seven years later, the career path she chose has not only a name—environmental data science—but a rapidly growing array of opportunities. Today, Jamie supports students who are looking to be part of the future of this field as coordinator for the Master of Environmental Data Science program, a new addition to the professional master’s programs offered at the Bren School.

“My first exposure to data science was through my MESM degree at Bren, and the master’s group project was my first opportunity to get my hands dirty with code. It was so powerful to realize what I could do with a programming language—the questions I could begin to ask and find answers to,” she says. 

Those questions range from the relatively narrow—such as tracking migration patterns for a particular species or evaluating biodiversity in a limited area—to the seemingly impossible to answer. At NCEAS, Jamie worked on the Ocean Health Index, which brings together diverse data sets to measure ocean health.

“There are a lot of different components that the Index measures,” Jamie says. “From biodiversity and water pollution, to human relationships with the ocean via tourism, recreation, and jobs. The OHI synthesizes nearly 100 different data layers every year. So, we built it using code that can just be updated and re-run year after year. That reduces the amount of work it takes to make a project like this possible and viable over time.”

Building an Environmental Data Science Community

When she started out, Jamie found that working in a new field brought fresh challenges every day—with few established resources to turn to for answers. Fortunately, she had a strong network from her master’s program to work through the challenges of applying data science tools to solve environmental problems.

“My peers were my biggest influence from Bren,” she says. “A group of us graduated together and started working on similar environmental data science problems. We were just reaching out to each other informally with our coding questions, and then we realized it would be a lot better if instead of learning separately, we could learn data science skills together.”

From this, an environmental data science study group known as EcoDataScience was born at UC Santa Barbara. In 2015, about 10 people—Bren alumni and a couple of scientists from NCEAS—started regularly meeting for monthly lunchtime workshops on data science tools useful for environmental science research.

The group expanded quickly, with more students and researchers from Bren and other UCSB departments attending each month, highlighting a great need that EcoDataScience was helping to address. Today, EcoDataScience has an online Slack community of nearly 500 members from Santa Barbara and across the world, a space where environmental data scientists can ask technical questions, share events, highlight new research, and find community.

“Data science is prevalent in nearly all industries, so there is a plethora of data science support through online communities. But without the environmental context, it can be difficult for scientists to get good answers to their coding questions. Environmental data is a broad suite of information that can include things like satellite imagery, ecological field data, location information from wildlife tracking devices, climate projections, species observations, and historical precipitation measurements, just to name a few.

“So the large scope of environmental data creates interesting challenges when it comes to accessing, working with, and storing the data. EcoDataScience provides an avenue for people to get help from folks who may have encountered the same issue or worked with a similar dataset,” Jamie says.

Advancing Environmental Data Science at Bren

Having seen firsthand the difference a strong network made for a career in environmental data science, Jamie was thrilled to return to Bren formally in the role of Master of Environmental Data Science Program Coordinator. With the first MEDS cohort graduating in 2022, Jamie’s new role is focused on supporting student success in a new program. She works with staff, faculty, and students across Bren to ensure that MEDS students are getting what they need to succeed.

“The MEDS program is for people with an environmental background who are seeking data science training that is directly applicable to addressing environmental issues in order to advance, or maybe pivot, their careers. Our courses are designed to get them up and running with a bunch of different tools that they can feel confident implementing once they go back onto the job market,” she says.

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Outside of research and academics, a lot of industries are seeing that data is power, so you need people on your team to be able to work with that data, ask questions of the data, and communicate the data.

Jamie notes that her focus on student success is shared among her colleagues, each looking to support students through their respective departments, from administration into the classroom.

“I think anyone can learn data science,” she says. “It’s true that these subjects can be intimidating and overwhelming. We’re lucky to have faculty who care about our students, who will explain these complex subjects over and over again until students get what they need.”

Given her wide-ranging day-to-day set of responsibilities, Jamie credits her own MESM degree and experience with helping in her new position. “In our programs, you have to work as a team. That collaborative attitude I learned through the MESM program definitely carries through into my new role.”

Creating a Program for the Future of Environmental Data Science

Since starting her career as an environmental data scientist, Jamie has seen the field evolve, grow, and influence environmental science and management in important ways.

“My role at NCEAS gave me the opportunity to do really interesting research in a unique academic data science role,” she says. “Typically a lot of academic research is done by graduate students, post-docs, or principal investigators. But more and more academic institutions are hiring data science positions, like mine, as a core member of their research team. Data science has pushed environmental research to be more open, reproducible, and accessible.”

“Outside of research and academics, a lot of industries are seeing that data is power, so you need people on your team to be able to work with that data, ask questions of the data, and communicate the data. Without that tool set, you’re at a disadvantage now.”

Because of these changes, the first MEDS cohort will find a very different job market than Jamie experienced, with opportunities in a wide variety of fields.

“When I graduated, I couldn’t even really articulate the job that I wanted. We didn’t have the vocabulary for it,” she says. “Now, you see these positions all the time: data scientist, data analyst, data engineer, and they’re all over the place. USGS has a fantastic data visualization team. Nonprofits like the Nature Conservancy are defining data science roles within their organizations. Corporations are bringing this specialization in house—for example, Lego recently hired an environmental data scientist. Established environmental consulting firms are adding data science specialists, and new analytical consulting firms with an environmental data science focus are popping up all the time.”

As the field continues to grow and change, Jamie says that one thing remains constant for those looking at careers solving environmental problems.

“Your peers are one of  your biggest strengths when it comes to making a career move or finding a job. We have a great Bren community and network. I got my job because of someone I graduated with, and I started EcoDataScience with my peers. I always tell students to invest in people and get to know each other because that’s the biggest thing that you’ll take away after graduation.”