Mark Anderson
Data Scientist
Kingston, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolMark Anderson is a data scientist with a Ph.D. in particle astrophysics who blends deep research rigor with 9 years of production software experience, primarily in Python and C++ on Linux. He has built and deployed deep learning pipelines to process TB-scale detector data, led end-to-end research projects, and modernized internal software stacks for collaborative teams. Notable applied work includes a Statistics Canada internship where he automated outlier detection and crude oil price forecasting, and a genomic clustering study exploring methylation-based prostate cancer biomarkers. A proven mentor and organizer, he founded a group to adapt detector methodologies, helped architect modular Monte Carlo simulation software for COVID-19 modelling, and regularly runs workshops to improve coding practices. Now at Larus, he’s looking to transfer his multidisciplinary experimental and ML toolkit into industry challenges that demand robust, maintainable systems.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at Queen's University
Github Skills (31)
recipe9
python9
machine-learning9
deep-learning9
shape-analysis8
tensorflow8
neural-network8
data-science7
discrimination7
binder7
pulse7
binderhub7
mybinder6
deep-neural-networks5
ml5
Programming languages (5)
Github contributions (5)
GePPCLab/NN-PSA-tutorial
May 2022 - Jun 2022
A tutorial on using TensorFlow to build neural networks for pulse shape analysis and discrimination.
Contributions:37 commits, 25 PRs, 13 pushes in 1 month
deep-learningdiscriminationneural-networkspulseneural-network
Queens-Physics/quaboom
Jun 2020 - Feb 2023
Hosting of our COVID-19 modelling efforts and data
Contributions:1 review, 159 commits, 1 PR in 2 years 9 months
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