Soung Low

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A data scientist working in the financial industry with an interest in AI safety and model risk.

Professional Experience

I work as a Model Risk Data Scientist at NatWest Group where I review, test, and validate AI models across different functions of the bank, such as fraud, financial crime, and marketing. With my prior role as a Data Scientist at Amplifi Capital, I have experience in retail lending, particularly the approval and pricing of loans and savings products using credit bureau data.

Personal Interest

I identify as a social data scientist, who is interested in the intersection of data science and political communication. Substantively, my research focuses on political representation, inequalities and stereotypes (particularly on the Malaysian political sphere), and public opinion. Methodologically, I focus on natural language processing and quantitative textual analysis for multilingual texts, such as news, parliamentary speech, and social media.

Education

I hold an MSc in Applied Social Data Science with Distinction from the London School of Economics and Political Science (UK), and a BSc in Economics from Feng Chia University (Taiwan), where I ranked first in my cohort.

News

May 20, 2024 Participated in the Data Study Group for Mastercard: “Measuring Fairness in Financial Transaction Machine Learning Models” at the Alan Turing Institute, UK (Report).
May 12, 2023 Presented “Unveiling Racial Stereotypes in the Malaysian News using Word Embeddings” at the 5th International and Interdisciplinary Conference on Quantitative and Computational Analysis of Textual Data (COMPTEXT 2023).
May 7, 2022 Presented “Wanita in Parliaments: The attitude of Malaysian MPs towards women” at the 4th International and Interdisciplinary Conference on the Quantitative and Computational Analysis of Textual Data (COMPTEXT 2022).
Nov 11, 2021 Presented “The Hashtag Activism of Milk Tea Alliance on Twitter: A Mixed-Method Study” at the 12th Asian Conference on Media, Communication & Film (MediAsia 2021).