Hello and welcome!
Who am I?
I’m Marlin Figgins, a soon-to-be PhD graduate from the University of Washington’s Department of Applied Mathematics and the Bedford lab at the Fred Hutchinson Cancer Center. My expertise lies at the intersection of statistical modeling, machine learning, and applied mathematics, with a focus on solving complex problems in evolutionary biology and public health. I am eager to apply my expertise to create scalable solutions that drive measured, effective, and fair action!
What do I do?
During my time at the University of Washington and Fred Hutch, I’ve come to believe scientists should seek to transcend traditional research boundaries. This has led to me spearheading interdisciplinary projects, collaborating closely with software engineers to translate complex models into scalable and user-centric tools such as evofr and forecasts-ncov. These projects not only advance our ability to understand, forecast, and monitor viral evolution, but also show how cross-functional collaboration can lead to scientific and practical advancements that can meaningfully improve decision-making.
Current goals
As I transition from academia to the industry, I’m looking for opportunities where I can contribute my expertise in machine learning, statistical analysis, and software engineering to tackle complex problems in any domain. Whether as a research scientist in (bio)tech, a machine learning engineer, or a data scientist, my goal remains the same: to deliver impactful results through innovation, mentorship, and a dedication to technical excellence. I believe that the fusion of quantitative science and domain knowledge is key to solutions that are not only effective but also transformative.
For a deeper dive into my professional journey and projects, feel free to explore my Research page or reach out directly via email. Hopefully, we’ll get to work together to build something new and make a difference.
Get in contact?
My personal email is marlinfiggins [at] gmail [dot] com, but I can also be reached mfiggins [at] uw [dot] edu.
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