Scholar
Soung Low
Google Scholar ID: CaY7O_YAAAAJ
Data Scientist, NatWest Group
Citations & Impact
Citations
2
H-index
1
i10-index
0
Publications
2
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Completed an 8-week AI Safety course (AI Alignment Track) by AIS Collab and received a Certificate of Completion; Participated in the Data Study Group for Mastercard: 'Measuring Fairness in Financial Transaction Machine Learning Models' at the Alan Turing Institute, UK; Presented 'Unveiling Racial Stereotypes in the Malaysian News using Word Embeddings' at COMPTEXT 2023; Presented 'Wanita in Parliaments: The attitude of Malaysian MPs towards women' at COMPTEXT 2022; Presented 'The Hashtag Activism of Milk Tea Alliance on Twitter: A Mixed-Method Study' at MediAsia 2021.
Research Experience
- Model Risk Data Scientist at NatWest Group, reviewing, testing, and validating AI models across different functions of the bank, such as fraud, financial crime, and marketing. Previously, a Data Scientist at Amplifi Capital, working on retail lending, specifically the approval and pricing of loans and savings products using credit bureau data.
Education
- MSc in Applied Social Data Science with Distinction from the London School of Economics and Political Science (UK); BSc in Economics from Feng Chia University (Taiwan) where he ranked first in his cohort.
Background
- A data scientist with an interest in AI safety and model risk. Research interests include political representation, inequalities and stereotypes (particularly in the Malaysian political sphere), and public opinion. Methodologically focused on natural language processing and quantitative textual analysis for multilingual texts.
Miscellany
- Identifies as a social data scientist, interested in the intersection of data science and political communication.
Co-authors