Senior Machine Learning Engineer

• May 2022 - Present

Senior Data Scientist

• Apr 2021 - May 2022

Led key innovation areas for the applications of data science in the organization, including the modernization of document processing using state-of-the-art NLP models, the development of malware classification by using deep neural networks, and the development of projects to support cyber network defense operations using anomaly detection algorithms.Designed the authentication/authorization framework for data science products by using Envoy, Keycloak, and OPA, enabling secure and maintainable delivery of analytics.Collaborated with infrastructure teams to support the containerized deployment of data science products on Kubernetes and Rancher, enabling the faster delivery of analytics.

Data Scientist

• Oct 2017 - Apr 2021

Research and develop machine learning (ML) algorithms, prototypes and solutions to solve critical business requirements, including developing an analytics application by using Docker, Streamlit, Flask, and ArangoDB to automatically detect signals of interest from dynamic graph and behavioral data, improving the efficiency of current methods by 600%.Explore and analyze large scale datasets to develop new use-cases and potential areas of research to maximize data yield, including enhancing organizational computer network defense capabilities by applying unsupervised learning techniques like Gaussian mixture models and Bayesian changepoint detection to detect anomalies and changes in large datasets, achieving analysis of terabyte-scale datasets efficiently.Identified bot campaigns on Twitter by using random forest classification models to analyze tweets and user profiles, achieving an F1-score of 95% and the detection of campaigns of interest in the wild.

Research Project : Deep Learning and Bayesian Ranking in Variant Calling

• Jun 2016 - Oct 2017

Implement deep ensemble learning pipeline for variant calling. Developed a pipeline for generation and analysis of artificial variant call datasets. Implement deep ensemble learning pipeline for variant calling. Developed a pipeline for generation and analysis of artificial variant call datasets.

Assistant Strategist

• May 2016 - Aug 2016

Strategy Analysis • Developed recommendations for five to ten year strategic shifts in Singapore’s technology and science policy -including authoring two internal papers • Engaged with stakeholders in A*STAR, NRF and other ministries to discuss key technological disruptors and their broad policy implications Data Analysis and Visualisation • Performed data collection and analysis for emerging strategic issues and presented findings in general staff meeting • Developed new data visualisation methods for internal intra-office data streams

Research Intern

• May 2015 - May 2016

Statistical Analysis and Data Processing • Performed multivariate analysis on hotel water consumption datasets, using statistical tools such as principal components analysis and factor analysis • Submitted a technical report to PUB analyzing the determinants of hotel water consumption in Singapore Sector-based Research and Analysis • Researched on the water provision industries of different countries, in terms of studying key players and analysing potential risk factors involved in national domestic water provision

Research Intern

• May 2013 - Aug 2013

• Performed and prepared experiments critical to a project for neurogenesis, and helped in the process of establishing a knockout line of zebrafish for the gene mdka1. • Performed and prepared experiments critical to a project for neurogenesis, and helped in the process of establishing a knockout line of zebrafish for the gene mdka1.