Peer-reviewed publications on labor market dynamics, skill prediction, and machine learning applications in economics.
Nik Dawson, Marian-Andrei Rizoiu, Mary-Anne Williams
A machine learning-based job transitions recommender system that predicts career pathway probabilities using skills data from 8+ million Australian job ads. Includes a leading indicator of AI adoption across industries.
View publicationNik Dawson, Sacha Molitorisz, Marian-Andrei Rizoiu, Peter Fray
Longitudinal analysis of 3,698 journalism job ads revealing the industry crisis. Findings include worsening gender inequity, rising demand for journalism skills despite job losses, and COVID-19's compounding effects.
View publicationNik Dawson, Marian-Andrei Rizoiu, Benjamin Johnston, Mary-Anne Williams
Machine learning models achieving 83% accuracy in predicting occupational skill shortages using job ads data and employment statistics. Identifies key predictive features including hours worked, education, experience, and salary.
View publicationNik Dawson, Marian-Andrei Rizoiu, Mary-Anne Williams, Benjamin Johnston
A data-driven method to detect skill shortages in real-time using job advertisements. Proposes five key variables: posting frequency, salary levels, education requirements, experience demands, and job posting predictability.
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