Education
-
Master of Data Science for Public Policy (Merit Scholar, GWA: 1.5)
Hertie School of Governance in Berlin (September 2021 — June 2023) -
Master of Science in Statistics (9 units completed, GWA: 1.25)
University of the Philippines — Diliman (September 2020 — June 2021) -
Bachelor of Science in Statistics (Cum Laude, GWA: 1.717)
University of the Philippines — Diliman (June 2012 — June 2016)
Professional Experience
-
Data Scientist
Compass Lexecon (August 2022 — present) -
Research Assistant
WZB Berlin Social Science Center (October 2021 — July 2022) -
Economic Research and Statistics Consultant
Asian Development Bank (April 2019 — August 2021) -
Competition Policy Consultant
Philippine Competition Commission (February 2021 — April 2021) -
Competition Policy Researcher
Philippine Competition Commission (November 2016 — April 2019)
Skills
Programming Languages: R, Python, SQL (sqldf and SQLite in R), LaTeX (Overleaf)
Programming Tools: RStudio, Anaconda, Github, VS Code, Spyder, Jupyter Notebook, Google Colab, Power BI
Statistical Tools: STATA, CSPro, SAS, Eviews, SPSS
Version Control: Git
Communication: Fluent in English and Tagalog
Publications
Arbo, M.A.G. (2023). Predicting merger decision outcomes of the European Commission: A Natural Language Processing and Machine Learning approach. Thesis for Master of Data Science for Public Policy. Hertie School.
Helble, M., Lee, O.K., Arbo, M.A.G. (2020). How (Un)affordable is housing in developing Asia? International Journal of Urban Sciences. doi: 10.1080/12265934.2020.1810104