Sophie Laturnus
Berlin, Germany
Summary
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SeniorSophie Laturnus is a data scientist with 15 years of experience bridging academic research and industry, currently applying computational methods to biopharma problems. With a PhD in Computational Neuroscience and hands-on roles at Bolt, she has built production ML systems for geospatial and traffic problems—migrating ETL to PySpark, optimizing ETA models, and shipping a pickup-location recommender. Her research background includes representing neural morphologies to link cellular form with function and genetics, and she brings strong statistical validation, visualization, and Bayesian interests to applied work. Passionate about sustainability, she self-studied soil regeneration and water restoration, which informs a practical, systems-level approach to problem solving. Fast-learning and collaborative, she combines domain curiosity with clean-code practices and growing expertise in graph neural networks.
15 years of coding experience
Github Skills (57)
feature-extraction10
glmnet10
python9
stochastic-processes9
biomedical9
neuroscience8
relational-model8
electrophysiology8
r8
computational-neuroscience8
journal7
datajoint7
machine-learning7
data-integrity7
metadata-management7
Programming languages (8)
Github contributions (5)
berenslab/MorphoPy
Dec 2017 - May 2021
A Python package for feature extraction of neural morphologies
Contributions:347 commits, 19 PRs, 181 pushes in 3 years 6 months
feature-extractionpython
Visdoom/mocapPlayer
Aug 2013 - Jan 2014
Contributions:21 commits in 5 months
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