Leonard Thong
Software Engineer at Google
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolLeonard Thong is a software engineer with eight years of experience building infrastructure and product features across leading tech companies and startups. He has shipped low-level infrastructure at Google and independently developed a Google Play feature used by billions of Android users, while also contributing to AR content tooling at Meta Reality Labs. As the first engineering hire on Monoceros’s trading platform, he designed and launched a full trading stack including screeners, scanners, and alerting systems. His background spans production-grade systems—from a static analysis engine serving thousands of enterprise customers to integrating lab systems with ML at PathAI—and includes a track record of hands-on product ownership. Based in New York and trained at Georgia Tech, he combines systems thinking with product sensibility and a proven appetite for solving practical problems end-to-end. An avid self-directed learner, he even applied quantitative trading and sentiment analysis to grow a personal portfolio three-and-a-half-fold, showing a knack for data-driven decision making.
8 years of coding experience
3 years of employment as a software developer
High School Diploma, High School Diploma at Various High SchoolsBachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Georgia Institute of Technology
English, Chinese
Github Skills (19)
pattern-recognition9
sequence9
stock-analysis9
sequence-labeling8
classify8
orange8
mls7
labeling7
lda7
machine-learning7
sentiment-analysis7
sentiment7
flask6
nltk6
refer5
Programming languages (3)
Github contributions (5)
leonard-thong/stock-sentiment-bot
Jul 2020 - Mar 2021
An application that performs sentimental analysis from scraped data to classify stocks into three separate categories (Bullish, Bearish, or Neutral).
Contributions:111 commits, 1 PR, 103 pushes in 8 months
orangepythonldastock-analysisflask
leonard-thong/learning-plus-plus
Feb 2020 - Apr 2021
A program that utilizes machine learning to analyzes lecture videos or typed notes to detect important keywords the user may need to refer.
Contributions:11 commits, 1 PR, 6 pushes in 1 year 2 months
notespythondata-sciencedeep-learninglecture-videos
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