Please check the PDF version of my resume on this link.
- dbt Fundamentals - dbt labs, 2023
- Microsoft Certified: Azure Data Scientist Associate - Microsoft, 2022
- Microsoft Certified: Azure Data Engineer Associate - Microsoft, 2022
- AWS Certified Cloud Practitioner - Amazon Web Services, 2022
- Discrete Choice Analysis: Predicting Market Demand - MIT, 2021
- Scalable Machine Learning with Apache Spark - Databricks, 2021
Data Analytics Engineer - Data Analyst - Johnson Controls - Australia:
Oct 2021 - Present
Develop Dynamic Pricing Models; Margin and Conversion rate optimisation; Customer churn modelling; Perform data analysis and build various KPIs and BI dashboards; Improve data quality, data governance and data security; Build and deploy End to End ML applications on Microsoft Azure.
Data Science Associate Instructor - Monash Data Fluency - Australia:
Jul 2021 - Dec 2022
Prepared technical materials; Taught hands-on workshops on machine learning, data analysis with Python, and data visualisation (Power BI) for professional staff and researchers at Monash University; Led a group of four instructors.
Data Analyst Intern - Domain Group - Australia:
Aug 2018 - Nov 2018
Developed customer clustering models for marketing and sales teams; Performed data analysis using SQL, ETL, Python; Building various dashboards with Tableau.
PhD Candidate - Machine Learning for Transport Systems - Monash University - Australia:
Feb 2020 - Feb 2023
Topic: Machine learning for transport systems; Activity-based Agent-based models. Supervisors: Prof. Hai Vu, Prof. Graham Currie.
Master of Information Technology - Macquarie University - Australia:
Feb 2017 - Feb 2019
Core units: Machine Learning, Data Mining, Information Systems, Security Management; GPA 6.733/7 (4.0/4.0); Top one postgraduate student; Academic Excellence Award.
Bachelor of Information Technology - Hanoi University of Science and Technology - Vietnam:
Aug 2005 - Jul 2010
Core units: Probability and Statistics, Algebra and Analytic, Numerical methods, Discrete Mathematics, Artificial Intelligence, Data structures and algorithms, Software Engineering. GPA 8.3/10; High Distinction; Top 3% of the Faculty.
Update: Feb 2023