From pipettes to pipelines: Five career gems from a data scientist
Ysis Wilson-Tarter shares her professional adventure at the forefront of biology and technology.
Ysis Wilson-Tarter says she’s “been in the game” for 15 years now, but she exudes the energy and enthusiasm of someone fresh on the scene.
“I think synthetic biology has definitely lived up to the hype, and then some,” she says. “And in the same way that synbio has taken pipettes out of our hands and let lab scientists work on more interesting things, now I see AI doing the same thing for coding — automating and organizing all the tedious tasks so that we can ask better questions and actually learn something from it.”
Ysis is a Data Engineer at Absci, where her work involves bringing together various AI pipelines, data models, and analyses with the ultimate goal of creating better biologics for patients, faster.
This month, she took a moment from that work to give the keynote address at this year’s Women in Data Science Conference at UC Berkeley, which brings together scientists and professionals to discuss the latest in data science across many domains. Ysis shared her career adventure from pipettes to data pipelines and hinted at the endless possibilities when it comes to data science and bioscience.
Just start somewhere
Ysis began her journey in science at the Dana Farber Cancer Institute at Harvard Medical School, where she started as a self-described “lab mule” in the wet lab, pipetting in the days before automation.
“We were still performing experiments by hand and collecting data manually,” Ysis says. “Flash forward to the present, and most of that grunt work is done by lab machines connected through IoT.”
As a young scientist at the time, Ysis says she really didn’t get too much about what was going on. Years later, using barcode fusion genetics in an industrialized setting for producing medicines, she is gratified to see how the lab science has matured and come together.
Ysis explored a wide range of experiences during this time: she developed her statistical chops working on MRI technology at Yale, and she learned user interface and engineering skills working on safe driver technology at Ford. Her biggest takeaway from this period: “Just do something and learn from it. You don’t have to do it forever. Don’t worry about changing your mind. Your time will never be wasted so long as you’re building transferable skills. You’ll always be getting closer to your personal professional sweet spot with every iteration.”
You don’t need to be a data scientist to do data science
Ysis’s first job after college was working as a software engineer at Athena Health.
“Our claim to fame was creating the first health app for the iPhone,” she says. “Patients and doctors could share information to check for adverse drug interactions before doctors prescribed medications. The app also had calculators for things like BMI and cholesterol.”
In this role, she learned a lot about NoSQL databases like neo4j, Cassandra, and Elasticsearch, as well as how to program in functional languages like Closure.
“At this point in my career, I also learned the expression ‘drinking from a firehose,’” she says. “Things were coming at me fast, and I was learning to do a lot of data science, even though I was technically a software developer.”
This brings Ysis to her next career takeaway: You don’t need to be a data scientist to do data science. “There are tons of roles out there that involve data science, whether it’s a software engineer, a data engineer, a developer, or an analyst. You will be able to practice data science depending on the role you take on.”
Imposter syndrome is real, but it’s not true
As her professional journey continued, Ysis found herself at some of the best-known names in biotech. At Zymergen (now Ginkgo Bioworks), she built tools to simplify the experimental workflow throughout the entire design-build-test-learn cycle, including lab management systems (LIMS). As a computational scientist, she was engineering lab processes in much the same way the company was engineering the productivity of organisms. She went on to Amyris, where she was immersed in synthetic biology and LIMS in using biology to make chemistry more sustainable. And in 2021, she earned her role at Absci as a Data Engineer, where she continues to help create better biologics for patients faster.
One takeaway from these role shifts: impostor syndrome is real, but it’s not true.
“At companies like these, you are on the bleeding edge, where you can’t simply Google the answers,” she says. “There will be a lot of onboarding, and you’ll start to feel like maybe you don’t belong there. It will be hard to figure things out. That’s normal, it happens to everyone. You just have to hang on and not freak out. You’re not an impostor.”
There is no perfect balance
Ysis also points out that at companies like Absci, Aymris, and Ginkgo — at the intersection of fields like biology, computer science, and data science — it’s easy to feel like you need to be an expert in all three. Ysis believes collaboration is the new superpower — the ability to turn to your colleagues and let them help you solve multidisciplinary problems.
“There is no magic unicorn who is good at everything,” she says. “I’ve worked with coders that started off with just a CS background and later got interested in bio. I’ve worked with pure biologists without any computational background who got it once they joined the company. I’ve even worked with an astrophysics Ph.D. who came into biology and ended up loving it and thriving. So the idea that there is a perfect balance or a perfect background — that’s a complete unicorn myth.”
Beyond developing the many facets of her professional expertise, Ysis still makes time to volunteer with Black Girls Code, a non-profit that aims to teach a million young women to code by 2040.
“Statistically, I shouldn’t be here,” she says. “I grew up in a rough part of New York City, and I’m part of just about every intersectional group you can think of. Young people may not know what’s possible until they see someone else doing it. So I want people to see that I’m here because that visibility might inspire someone else and help them realize their story.”
Never stop learning
For her next act, Ysis will be teaching a course at UC Berkeley School of Information on data science. So, on top of building pipelines at Absci, she’ll be teaching others how to build their own pipelines. This brings Ysis to her final takeaway: Never stop learning.
While working full-time herself, Ysis earned her Master’s degree at Johns Hopkins. “It may seem like a lot, but actually it ended up being pretty helpful because many employers in tech will help pay for your tuition expenses. They want you to build on your knowledge because it makes you a more valuable employee.”
That’s true at companies like Absci, where it takes a state-of-the-art wet lab, cutting-edge data science, and a diverse and talented team to push the limits of science in a way that no one has done before — because that’s how we will save lives.
“There are endless possibilities when it comes to data science and bioscience,” Ysis says, “and we’re only at the tip of the iceberg.”