Labor Market Landscape Modeling with Knowledge Graphs

Session Track: Data Intelligence

Session Time: 08:15 am - 08:30 am November 6

Session description

In this session, the speakers will present an approach to modeling and predicting Singapore’s labor market using a snapshot-based knowledge graph. Amid rapid workforce transformation and AI-driven job disruption, the session will demonstrate how knowledge graphs can reveal how the labor landscape is evolving. By integrating expert-curated and real-time labor data, this approach provides valuable insights for policymakers and developers. You will learn how to build and use knowledge graphs to integrate diverse datasets, perform graph-based reasoning, and extract actionable insights. The session will equip you with both the conceptual foundations and practical tools to develop similar knowledge graphs.

Speakers

Lois JI

Data Scientist, GovTech

Lois is a data scientist with a degree in Economics and works at GovTech in Singapore. In the past seven years, she has gathered experiences working in startups, corporates, and now the Singapore government. Her area of expertise lies in applied NLP/LLMs for textual data analysis, where she seeks to strike a balance between practical functionality and technical sophistication. Her newfound interest is in combining graph with generative AI for a more human-centric implementation of process automation.

Merson Cheong

Data Scientist, GovTech Singapore

Merson is a Data Scientist at GovTech, whose work involves extensive use of graph-based solutions with platforms such as Neo4j. He applies graph analytics to model labour market dynamics and has previously built graph systems to detect scams. His projects combine applied machine learning with graph technologies to enhance digital trust and support evidence-based policymaking.