Daniel Csaba
Quantitative Researcher -- Economist
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDaniel Csaba is a quantitative researcher and economist with a decade of experience applying causal inference, machine learning, and economic modeling to build data-driven algorithmic solutions for industry. Based in New York, he has been at QuantCo since 2019, translating rigorous academic training from a PhD in Economics at NYU into practical solutions across pricing, policy evaluation, and decision analytics. His background includes teaching econometrics, microeconomics, and Python-based data bootcamps, reflecting an ability to communicate complex methods to diverse audiences. Earlier research and open-source work on Bayesian portfolio models and statistical Python tooling signal a strong foundation in probabilistic modeling and reproducible research. Colleagues value him for combining theoretical depth with pragmatic engineering to turn causal questions into deployable analytics.
10 years of coding experience
1 year of employment as a software developer
Master's Degree, Economics, Master's Degree, Economics at Universitat Autònoma de BarcelonaDoctor of Philosophy (Ph.D.), Economics, Doctor of Philosophy (Ph.D.), Economics at New York UniversityBachelor's Degree, Applied Economics, Bachelor's Degree, Applied Economics at Eötvös Loránd University
Hungarian, Italian, German, Spanish, English
Github Skills (26)
conda-forge10
conda10
forge10
distributions10
smithy8
python7
quantitative7
economics5
prediction-model5
machine-learning4
sampling4
procedures4
density-estimation3
spring3
regression3
Programming languages (6)
Github contributions (5)
QuantEcon/rvlib
May 2016 - Jul 2021
Distributions for Python
Contributions:1 release, 115 commits, 10 PRs in 5 years 3 months
distributionspython
QuantEcon/econometrics
Dec 2016 - Feb 2017
Contributions:42 commits, 33 pushes in 2 months
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