Katherine Edgley
PhD Candidate
United Kingdom
Summary
👤
Senior🎓
Top SchoolKatherine Edgley is a data scientist and PhD candidate at the University of Edinburgh with nine years’ experience applying statistical modelling and machine learning to health and time-series data. Her research blends wearable technology and reproductive health to map symptom trajectories in endometriosis, drawing on strong quantitative training from an MSc in Computational and Applied Mathematics and a BA in Applied Mathematics. She has commercial experience de-identifying complex health datasets and building ML pipelines in Python and R, with practical AWS and SQL skills honed at Mirador Analytics and consulting roles. Katherine combines academic rigor with client-facing experience, having translated privacy and bias mitigation concepts into actionable recommendations for health data projects. An unconventional thread through her career is a background in humanities and immersive teaching, which informs her clear science communication and interdisciplinary approach.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Reproductive Health, Doctor of Philosophy - PhD, Reproductive Health at The University of EdinburghBachelor of Arts - BA, Applied Mathematics, Bachelor of Arts - BA, Applied Mathematics at Brown UniversityMiddlebury CollegeDeutsche Literatur und Philosophie, Deutsche Literatur und Philosophie at Humboldt University of Berlin
English, German, Latin
Github Skills (8)
linear-regression2
logistic-regression2
scikit1
regression1
python1
machine-learning1
data-science1
scikit-learn1
Programming languages (3)
Github contributions (5)
mohammeddonia/RSCAM-GradNoise
Mar 2019 - Apr 2019
Contributions:23 commits, 5 pushes in 1 month
katherineedgley/model-stats-extension
Apr 2020 - Apr 2020
An extension to scikit-learn linear_model that provides statistical analysis of linear regression results
Contributions:8 PRs, 18 pushes, 2 branches in 2 days
regressionpythonlogistic-regressiondata-sciencelinear-model
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