Sophia Lilleengen is an applied data scientist with a PhD in Astrophysics and a decade of experience turning complex scientific problems into robust, reproducible software and machine learning solutions. She has led Bayesian and neural modelling projects, secured GPU and event funding, and taught ML and scientific computing to 100+ students annually, blending research leadership with hands-on engineering. Her work spans open-source scientific packages, time-series forecasting of galactic interactions, and production-ready tools used by international research teams. Comfortable moving between Python, C/C++ integrations and high-performance compute environments, she excels at extracting actionable insight from messy data and mentoring others to do the same. Based in Manchester, she brings a rare mix of astrophysical domain expertise and practical data-product delivery for real-world impact.
10 years of coding experience
7 years of employment as a software developer
Master of Science - MS, Physics, Master of Science - MS, Physics at Heidelberg University
Doctor of Philosophy - PhD, Astrophysics, Doctor of Philosophy - PhD, Astrophysics at University of Surrey
Contributions:95 pushes, 1 branch in 5 years 9 months
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