Publication: Piloting a Machine Learning-Based Job-Matching Algorithm: Summary of Results from Pomerania
Date
2023-11-20
ISSN
Published
2023-11-20
Author(s)
Abstract
The objective of this note is to
present and discuss the findings of piloting a task-based
job matching tool developed by the World Bank and
implemented in partnership with the Regional Labor Office of
Pomerania, Poland. The aim of the pilot was to assess
whether simple ML-based tools could contribute to improve
the efficiency of PES delivery and job-seeking behaviors
compared to rule-based, knowledge-driven approaches. By
combining labor demand data from local occupational
barometers and the descriptions of tasks in the national
taxonomy of occupations, the tool provides jobseekers a menu
of potential jobs available in the local labor markets that
match the tasks performed in previous work experiences.
Results show that jobseekers were satisfied with the
proposed occupations resulting from the tool (as beyond
their thinking) and had the intention to expand job search
efforts, though job-seeking behaviors could not be
monitored. Career advisers recognized that the lack of
information on jobseekers’ education, skills, and
preferences limited the efficiency of the proposed job matches.
Link to Data Set
Citation
“Honorati, Maddalena; Ferré, Céline; Gajderowicz, Tomasz. 2023. Piloting a Machine Learning-Based Job-Matching Algorithm: Summary of Results from Pomerania. Jobs Notes; Issue No.17. © Washington, DC: World Bank. http://hdl.handle.net/10986/40628 License: CC BY-NC 3.0 IGO.”