Summary
Dickson Kwong is a Principal Data Scientist based in Melbourne with over a decade of experience architecting and scaling ML solutions across telco, marketplace, retail and energy sectors. He combines hands-on model development—real-time recommendations, propensity models, CTV engines—with MLOps and infrastructure-as-code practices to move projects from R&D into robust production on platforms like Databricks. At TPG Telecom and Airtasker he established coding standards, drafted MLOps frameworks, and led cross-functional initiatives that improved retention, pricing and lifetime value. A founder-level contributor to data product teams, he has a track record of building internal SDKs and standardized pipelines that raise team velocity and maintainability. Trained in mathematics and computer science at the University of Washington, Dickson pairs practitioner-level engineering discipline with business-focused impact and a history of coaching teams to adopt production-grade ML.
11 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.) Mathematics and Computer Science, Bachelor of Science (B.S.) Mathematics and Computer Science at University of Washington
Data Science Data Science, Data Science Data Science at General Assembly