Shaw Lu is a Staff Machine Learning Engineer based in Palo Alto with eight years of experience building production ML and ranking systems at scale, primarily at Coupang. He combines strong engineering chops in Spark, TensorFlow, Flink, Kafka and graph technologies with hands-on SQL expertise—evidenced by his Beyond-LeetCode-SQL repository and extensive feature engineering work for lookalike models. Shaw has driven measurable business impact through AB tests and production experiments that improved GMV and conversion, and holds a patent for dynamic community tracking from his fraud-detection work. With an MS from Stanford in Management Science & Engineering and a background founding a startup, he blends product-minded experimentation with deep technical implementation. Outside work he writes for Towards Data Science and pursues pottery, reflecting a creative curiosity that complements his systems-first approach to ML.
8 years of coding experience
5 years of employment as a software developer
BS, Mechanical Engineering, GPA 3.98 (magna cum laude), BS, Mechanical Engineering, GPA 3.98 (magna cum laude) at New York University Abu Dhabi
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Sofia University
MS, Management Science & Engineering, GPA 3.85, MS, Management Science & Engineering, GPA 3.85 at Stanford University
Analysis of SQL Leetcode and classic interview questions, common pitfalls, anti-patterns and handy tricks. Sample databases.
Role in this project:
Database Engineer / Database Administrator
Contributions:88 commits, 14 PRs, 148 pushes in 2 years 9 months
Contributions summary:Shaw primarily contributes SQL solutions to LeetCode problems related to database querying and data analysis. Their work focuses on writing SQL queries to solve various problems, including those involving joins, aggregations, and window functions. The user's commits demonstrate a strong proficiency in SQL, with solutions addressing problems of varying complexity, from basic select statements to more complex analytical queries. The contributions cover a wide array of SQL features.
A iOS accounting app for personal finance. Server code (PHP) connects the mobile app to a MySQL database. A Python notebook is also provided for SQL analytics and visualization.
Contributions:1 review, 1 PR, 9 pushes in 1 year 11 months
accountinganalyticspythonmysqlnotebook
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