Nicholas Carrara

Senior Data Scientist, Specialist Senior

Sacramento, California, United States
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Summary

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Senior
🎓
Top School
Nicholas Carrara is a Senior Data Scientist and machine learning research scientist with a Ph.D. in Physics and eight years of experience applying CV, generative AI, reinforcement learning, and scalable ML systems to scientific problems. He combines theoretical contributions—such as first-principles mutual information derivations and a high-dimensional MI estimator using Monte Carlo Tree Search—with hands-on engineering of multi-GPU pipelines for sparse 3D reconstruction and production-ready ML code. At UC Davis and national labs he led multi-institutional experiments (DUNE, ARTIE, MArEX) and built ML-driven signal detection and reconstruction tools for particle and neutron physics. Equally comfortable with contrastive learning, GNNs, transformers, and diffusion models, he bridges research and product by optimizing large-scale simulation stacks (LArSoft, PyTorch) for real experimental throughput. Based in Sacramento, he’s now applying this blend of theoretical depth and systems engineering at Deloitte to build intelligent systems with measurable scientific and operational impact.
code8 years of coding experience
bookDoctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at University at Albany
bookAssociate of Science - AS, Biology, General, Magna Cum Laude, Associate of Science - AS, Biology, General, Magna Cum Laude at Hudson Valley Community College
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Github Skills (24)

simulate10
argon10
python-bindings10
modeling-tool9
energy9
simulation9
physics9
modeling9
nest9
python8
delaunay5
topological-data-analysis5
connectivity5
machine-learning5
topology5

Programming languages (4)

C++CJupyter NotebookPython

Github contributions (5)

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Contributions:255 pushes, 3 comments, 6 issues in 9 months
Scripts for installing and running the Arrakis module in LArSoft.
Contributions:6 PRs, 84 pushes, 1 branch in 1 year 7 months
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Nicholas Carrara - Senior Data Scientist, Specialist Senior