Working with the data science team of Burning Glass Europe (Italy), the European Training Foundation (ETF) collected and processed hundreds of thousands of online job vacancies over 8 consecutive months in 2020 (April-December). The data system uses ESCO as the reference for machine-classification of skills to provide insights on skills and occupational features and dynamics of the Tunisian and Ukrainian labour markets.
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The Intelligence Group, an international data and tech company, is holding a series of webinars to discuss labour market data-related topics. The first webinar was dedicated to ESCO. During the presentation, the ESCO team gave an overview of the classification, shared examples of the use of ESCO by implementers to run data analysis activities, informed on relevant news and presented the mission of current and future data science works. The presentation is available on YouTube, following the link below.
The Amsterdam-based social startup that develops an AI-driven solution building on the ESCO classification has proven its value for the international labour market, being awarded with an investment of EUR 1.5 Million from Rubio Impact Ventures. SkillLab’s model allows people to identify their unique skill set and connects them to education and employment opportunities, generating highly personalised career pathways.
In the period between mid-December 2020 and mid-January 2021, the Commission launched a consultation on a pre-release draft of the ESCO next major version (v1.1). The draft is an updated version of the classification. New concepts (occupations, skills, knowledge concepts) have been drafted following a one-year long process of research, feedback processing and discussion with sectoral experts and European associations. ESCO v1.1 will be published at the end of 2021, following a series of consultations with ESCO stakeholders including EU Member States.
The UK-based innovation foundation NESTA has built a recommendation algorithm to provide guidance on how workers (in the UK, France and Italy) can transition out of occupations that are most at risk of automation. The approach uses the ESCO classification to build detailed occupation profiles, measure occupation similarity, and identify viable, desirable and safe transitions.
The Inter-American Development Bank developed a machine learning model to analyse job vacancies in LAC countries using ESCO occupations and skills. This note is intended to be a starting point and set of considerations for policymakers who may be considering, or already embarking on, similar efforts to use ESCO or other taxonomical structures to help better analyse, understand and use skills-level information for decision making.
Following feedback received from ESCO implementers, a new section will soon be included in the ESCO portal to promote academic papers, articles or reports which make use of ESCO in their methodology. This will support the share of knowledge within the ESCO community and contribute to mutual learning among European and international actors.