Alexander Fry is a Machine Learning Engineer in Seattle with nine years of experience translating scientific rigor into actionable behavior-change solutions. Trained as an astrophysicist (PhD, University of Washington) and grounded in physics from UT Austin, he bridges complex data science methods and real-world product needs. At Tignis he applies ML to practical problems, building reliable pipelines informed by previous work at The Data Incubator and hands-on analysis of large-scale datasets such as Backblaze hard-drive failure data. His background in radio astronomy and simulation research gives him a strong foundation in probabilistic modeling, signal processing, and scalable computation. Known for turning positive intentions into measurable outcomes, he combines curiosity-driven research instincts with production-focused engineering.
10 years of coding experience
Doctor of Philosophy (PhD), Astronomy, Doctor of Philosophy (PhD), Astronomy at University of Washington
Bachelor of Science (B.S.), Astronomy, Physics, Bachelor of Science (B.S.), Astronomy, Physics at The University of Texas at Austin
Contributions:7 commits, 6 pushes, 1 branch in 5 years 9 months
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