Guillaume Drouart

Principal Data Scientist

Western Australia
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Summary

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Senior
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Top School
Guillaume Drouart is a Principal Data Scientist with nine years of cross-disciplinary experience applying Bayesian statistics and large-scale data engineering to problems in health, energy, environment and astrophysics. He led the operationalisation of a malaria risk stratification model for policy use, managed an international Indigenous multi-omics clinical trial with bespoke data governance, and built scalable tools for handling SKA-precursor radio astronomy datasets. Equally comfortable producing production-ready R packages and migrating models to AWS as he is writing Python Bayesian SED fitting code, he blends research rigor with productionisation skills. Based in Western Australia, he also drives practical sustainability efforts—helping estimate his institute’s carbon footprint—and bikes everywhere with his three children. Notably, his background in galaxy evolution taught him to solve needle-in-a-haystack problems at planetary scale, a mindset he brings to public health and energy-transition challenges.
code9 years of coding experience
job9 years of employment as a software developer
bookBachelor of Science (BS), Theoretical and Mathematical Physics, Bachelor of Science (BS), Theoretical and Mathematical Physics at Université de Poitiers
bookDoctor of Astrophysics, Galaxy Evolution, Doctor of Astrophysics, Galaxy Evolution at Université Paris Sud (Paris XI)
bookMaster of Science (MS), Astrophysics, Master of Science (MS), Astrophysics at Observatoire de Paris
languagesEnglish, French, Spanish
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Github Skills (17)

sampling10
mcmc9
python8
r-package8
spatial6
data-handling6
terra6
vector5
spatial-data5
geospatial5
r5
raster5
data-analysis3
gdal3
matplotlib2

Programming languages (2)

C++Python

Github contributions (5)

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gdrouart/MrMoose

Jul 2017 - Nov 2021

Contributions:35 commits, 26 pushes, 3 branches in 4 years 4 months
2022 ICRAR Data Science applicants exercise
Contributions:7 pushes in 1 day
pythonsciencedata-sciencemachine-learningapplicants
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