Summary
Jay Do is a Data Science Manager based in Sydney with 12 years blending academic rigor and production-grade engineering across AI, MLOps, and data platforms. A PhD-trained mechatronics researcher who writes production code, he has built and operated end-to-end ML systems and data platforms (BigQuery, dbt, Vertex AI, GKE, Airflow) used by hundreds of users and multiple enterprises including Westpac, Tabcorp, THE ICONIC and Endeavour Group. He routinely ships models to production with custom serving containers, serverless APIs and CI/CD, and has applied ML to churn, supply chain, vision, and vehicle routing problems. Known as a hands-on consultant and technical leader, he bridges stakeholder needs and modern tooling to scale analytics across teams. An under-the-radar strength is his space-tech CV experience—deploying vision algorithms to single-board computers for CubeSat-class platforms—reflecting broad systems-level expertise.
12 years of coding experience
7 years of employment as a software developer
Postdoctoral Computer Science, Postdoctoral Computer Science at University of Adelaide
bachelor Mechatronics, bachelor Mechatronics at Hanoi University of Science and Technology
Doctor of Philosophy (PhD) Mechatronics Robotics and Automation Engineering, Doctor of Philosophy (PhD) Mechatronics Robotics and Automation Engineering at Michigan State University
bachelor Robotics System Control, bachelor Robotics System Control at Korea Advanced Institute of Science and Technology
English, Vietnamese