David Guanhua is a data scientist with a decade of technical experience blending NLP, machine learning, and full-stack engineering across cloud and distributed systems. He has applied lexical and vector semantics, probabilistic and deep learning models (including Transformer-based NMT), and classic supervised/unsupervised methods in Python and R to productionized ML tasks, often leveraging PySpark, Spark MLlib, and AWS/GCP for scale. He complements modeling expertise with practical data engineering—building ETL pipelines in Oracle SQL, querying NoSQL with Spark, and creating BI dashboards in Tableau and OBIEE—as well as front-end and mobile experience in PHP/Node and Flutter. Educated across institutions in China, Korea, Singapore and the US (Boston University MSCIS), he pairs a multidisciplinary academic background with hands-on implementation. An active GitHub presence (leebond) surfaces his engineering-first approach to data science and product-focused solutions.
10 years of coding experience
Master of Science, Computer Information Systems, MSCIS, Master of Science, Computer Information Systems, MSCIS at Boston University
Bachelor of Engineering (B.Eng.) with Honours, Engineering Systems and Design, Bachelor of Engineering (B.Eng.) with Honours, Engineering Systems and Design at Singapore University of Technology and Design (SUTD)
Econometrics and Macroeconomics, 4.0/4.0, Econometrics and Macroeconomics, 4.0/4.0 at Hanyang University
Product Innovation and Design, Product Innovation and Design at Zhejiang University
Contributions:50 commits, 2 PRs, 5 pushes in 1 month
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