Ming-yuan Lu is a Senior Data Scientist with nine years of experience building production-scale data pipelines and analytics platforms, currently at Enigma Labs after leading data engineering efforts at The Wall Street Journal. He holds a PhD in particle astrophysics from the University of Wisconsin–Madison and brings a researcher's rigor to engineering problems, having developed C++ simulation and interferometric analysis tools for cosmic neutrino experiments. At WSJ he built a Scala/Spark streaming pipeline ingesting 40M+ events/day and optimized Postgres performance up to 25x while provisioning infrastructure with Terraform on AWS. His technical breadth spans Python, Scala, C/C++, Spark, Kafka/Kinesis, Druid, TimescaleDB and observability tooling, enabling rapid, cost-effective delivery of near real-time insights for product and editorial stakeholders. Colleagues rely on him to translate complex analytical needs into robust data schemas and streaming architectures, blending academic-caliber statistical thinking with pragmatic cloud engineering. An under-the-radar strength is his ability to fuse experimental physics techniques with large-scale data systems to solve unusual signal-processing and data-quality challenges.
10 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Particle Astrophysics, Doctor of Philosophy (Ph.D.), Particle Astrophysics at University of Wisconsin-Madison
Bachelor’s Degree, Physics, Bachelor’s Degree, Physics at National Taiwan University
Contributions:118 commits, 3 PRs, 104 pushes in 29 days
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