Alan Leggitt - Principal Data Scientist

Alan Leggitt

Principal Data Scientist

New York, New York, United States

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Summary

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Senior

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Top School

Alan Leggitt is a Principal Data Scientist with 12 years of experience applying mobile technology, big data, and signal processing to expand access to healthcare. Currently leading advanced analytics at CVS Health, he progressed through senior and lead data science roles designing clinical-grade algorithms and production pipelines for physiological data collected via smartphones. His background in neuroscience and physics informs work on biomarkers and EEG/MEG data—evidenced by contributions to the well-regarded MNE-Python project where he improved back-end handling of raw EEG data. Earlier roles at Vital Labs and academic research in cognitive neuroscience gave him hands-on experience running clinical validation studies and translating biosignals into actionable clinical insights. A former Army infantry team leader, he brings operational discipline and people-centered leadership to cross-functional teams. He combines academic rigor with pragmatic product delivery to move novel biometric research from lab prototypes into scalable healthcare solutions.

12 years of coding experience

14 years of employment as a software developer

B.S. Physics, B.S. Physics at University of San Francisco

Master of Science (MS) Neuroscience, Master of Science (MS) Neuroscience at University of California, San Francisco

English

Stackoverflow

Stats

662reputation

43kreached

7answers

7questions

Github Skills (12)

neuroscience10

python10

data-structure9

data-structures9

algorithms9

pandas6

flake6

csv6

amazon-emr6

excel6

vectorization6

numpy6

Programming languages (4)

RSwiftHTMLPython

Github contributions (5)

mne-tools/mne-python

Oct 2013 - Jul 2015

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

Role in this project:

Back-end Developer

Contributions:92 commits, 3 PRs, 19 comments in 1 year 9 months

Contributions summary:Alan primarily contributed to the back-end of the MNE-Python library, focusing on the `Raw` data class and functions related to EEG data rereferencing. They implemented new functionality such as adding a copy parameter to a rereference function, making it possible to modify data in place. They also refactored existing code, by changing a function from a method to a function.

visualizationneuroimagingneurosciencepythonstatistics

leggitta/leggitta.github.io

Jun 2017 - Aug 2023

Contributions:29 pushes, 1 branch, 3 issues in 6 years 3 months

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