Benjamin Datko

Data Scientist

Washington, District of Columbia, United States
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Summary

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Senior
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Top School
Benjamin Datko is a Data Scientist at Bloomberg Law with 11 years of experience applying machine learning, taxonomy design, and data engineering to legal research. He manages and modernizes classification for 3,500+ taxonomy categories across more than a million legal documents annually, moving systems from rule-based to hybrid ML pipelines to improve accuracy and scalability. His background includes a PhD in Chemistry and postdoctoral research at the U.S. Naval Research Laboratory, where he developed rigorous experimental and computational methods—skills he now applies to annotation workflows and training pipeline design. Benjamin is proficient in Python, SQL, Tableau, and multiple RDBMS, and contributes to open-source projects like NumPyro and PyAgrum, emphasizing reproducibility and documentation. He blends deep domain collaboration with subject-matter experts and engineers to make dense legal content discoverable and actionable. Based in Washington, D.C., he pairs scientific rigor with product-minded execution to drive measurable improvements in legal analytics.
code11 years of coding experience
job10 years of employment as a software developer
bookBachelor of Science (B.S.), Chemistry, Bachelor of Science (B.S.), Chemistry at Temple University
bookDoctor of Philosophy - PhD, Chemistry, Doctor of Philosophy - PhD, Chemistry at The University of New Mexico
bookHigh School Diploma, High School Diploma at Haverford High School
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Github Skills (46)

bayesian9
symbolic-algebra8
bayesian-inference8
python8
mcmc8
pandas8
pyro8
data-structure8
probabilistic-programming8
data-science7
pytorch7
variational-inference7
machine-learning7
gpu7
data-analysis7

Programming languages (3)

HTMLJupyter NotebookPython

Github contributions (5)

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bdatko/numpyro_play

Jun 2021 - Oct 2021

Contributions:62 commits, 29 pushes, 1 branch in 3 months
bdatko/.dotfiles

Sep 2024 - Dec 2025

Contributions:24 pushes, 1 branch in 1 year 3 months
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