Chloe Ransom is a Data Scientist and ML Engineer based in Zurich with eight years of experience bridging experimental particle physics and production ML systems. She holds a PhD from the University of Zurich and has driven novel calibration algorithms, automated large-scale time-series pipelines, and uncertainty modelling for international collaborations like GERDA and LEGEND. At Xovis she applies that research-honed rigor to building robust ML solutions, combining statistical insight with software engineering best practices. A skilled communicator and mentor, she has onboarded students and handed over complex projects to ensure long-term maintainability. Unusually for an ML engineer, her background includes hands-on hardware and DAQ work—calibrating PMTs and contributing to instrument design—giving her a practical appreciation for end-to-end data quality.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at University of Zurich
Computer Science, Passed with distinction, achieving full marks in the final examination, Computer Science, Passed with distinction, achieving full marks in the final examination at CERN School of Computing
Master of Physics (MPhys), Physics, First Class, Master of Physics (MPhys), Physics, First Class at University of Oxford
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