Hi, my name is Danh Phan. I am passionate in turning data into actionable insights. My goal are to develop data-driven products to solve real-world problems, and to help businesses make efficient science-based decisions.
As a Data Scientist at the Pacific service team, Johnson Controls Australia, my tasks involve developing Dynamic Pricing Models, optimizing Margin and Conversion rates, modelling Customer churn risks on Microsoft Azure, as well as performing data analysis and building various KPIs and BI dashboards.
I am experienced in Python, and have been a Data instructor at Monash Data Fluency, where I teach hand-one data-related workshops with Python, Git, Bash, and High-Performance Computing to research students and staff at Monash University. I love Bayesian statistics, and actively contribute to open-source projects like PyMC and Aesara on GitHub. I’ve worked on a Google Summer of Code project where I develop a module that supports Multi-output Gaussian Processes in PyMC.
I am also a PhD researcher at Monash University, working on Machine learning for intelligent transport systems. This research focuses on understanding people’s choice behaviors when selecting their activity locations and travel modes. In this research, I applied various Machine learning methods (Bayesian methods, choice models, tree-based, and deep neural networks) with econometrics modeling approaches.