Dongkyu Choi is a Seoul-based machine learning engineer with 9 years of experience building production-grade ML systems across fintech and platform companies. He designed Modelier, a feature meta management library that replaced tens of thousands of lines of SQL and helped consolidate legacy metadata into a single source of truth, and built scalable PySpark pipelines and custom deserialization to process high-volume feature data memory-efficiently. His models have driven measurable business impact—boosting home loan conversions to generate an estimated $1.3M weekly and doubling conversion rates for other key products—while also shipping targeting, income-prediction, and DSP/CTR solutions. With a background in economics and financial engineering from NYU and prior work at the Bank of Korea, he combines rigorous quantitative modeling (ASR, LSTM nowcasting, FX prediction) with hands-on engineering and product sensibility. He’s an all-time learner who routinely turns complex data and legacy stacks into reusable, developer-friendly tooling that accelerates modelers’ workflows.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Applied Science (B.A.Sc.), Information Statistics; Computer Science, 4.1/4.5, Bachelor of Applied Science (B.A.Sc.), Information Statistics; Computer Science, 4.1/4.5 at 한국방송통신대학교
Master's degree, Financial Engineering, 3.8/4.0, Master's degree, Financial Engineering, 3.8/4.0 at New York University
Bachelor of Business Administration (BBA), Business, 3.6/4.3, Bachelor of Business Administration (BBA), Business, 3.6/4.3 at Yonsei University 연세대학교
Bachelor's degree, Business Administration and Management, General, 3.56, Bachelor's degree, Business Administration and Management, General, 3.56 at Yonsei University
Contributions:20 commits, 6 PRs, 15 pushes in 2 years 2 months
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Dongkyu Choi - 머신 러닝 엔지니어 at Viva Republica (Toss)