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Hi there, I'm Youngmin πŸ‘‹

I'm a Data Scientist, Economist, Applied Scientist

  • πŸ‘€ I’m interested in causal inference, machine learning, predictive analytics, and experimental design.
  • πŸŽ“ PhD in Economics @ USC / MA in Economics @ Korea Univ. / BS in Mathmatical Sciences @ KAIST
  • πŸ”­ I was a Junior Military Officer @ ROKA (Republic of Korea Army)
  • 🌱 I’m currently learning from kaggle, data potcasts, linkedin learning and towards data science.
  • πŸ’žοΈ I’m looking to collaborate on causal inference and machine learning.
  • πŸ‹οΈ Workout everyday!
  • πŸ“« How to reach me: [email protected]

Connect with me:

youngminju.com youngminju | LinkedIn


Languages and Tools:

Visual Studio Code HTML5 Python R SQL MySQL JavaScript Git GitHub Terminal


πŸ“• Latest Project Posts

➑️ more project posts...


Youngmin Ju's Projects

algorithm-interview icon algorithm-interview

<파이썬 μ•Œκ³ λ¦¬μ¦˜ 인터뷰> 95가지 μ•Œκ³ λ¦¬μ¦˜ 문제 ν’€μ΄λ‘œ μ™„μ„±ν•˜λŠ” μ½”λ”© ν…ŒμŠ€νŠΈ

bundling_price icon bundling_price

Simple Numerical Study of Net Sale’s Gain from Bundling Price

causal-ml icon causal-ml

Must-read papers and resources related to causal inference and machine (deep) learning

part.odr.-endo-trt-obes-data-gauss-program icon part.odr.-endo-trt-obes-data-gauss-program

Ju, Y.M. and M.J. Lee. (2017). β€œControl Function Approach for Partly Ordered Endogenous Treatments: Military Rank Premium in Wage”, Oxford Bulletin of Economics and Statistics, 79: 1176-1194.

python-causality-handbook icon python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.

python-for-coding-test icon python-for-coding-test

[ν•œλΉ›λ―Έλ””μ–΄] "이것이 취업을 μœ„ν•œ μ½”λ”© ν…ŒμŠ€νŠΈλ‹€ with 파이썬" 전체 μ†ŒμŠ€μ½”λ“œ μ €μž₯μ†Œμž…λ‹ˆλ‹€.

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