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Online job portals collecting web vacancies have become important media for job demand and supply matching. They also represent a growing research area for the application of analytical methods to study the labour market using innovative data sources. This paper analyses Italian web job vacancies scraped from several types of Italian web job portals between June and September 2015. After describing how the occupations associated with each web vacancy (classification up to level 4) were identified and the related skills retrieved in texts using mixed supervised and unsupervised text mining approaches, we focused on job vacancies related to ICT and statistical positions. The principal aim of this paper is to describe these jobs in terms of the required skills that have emerged in the labour market from a demand perspective and to identify those skills that best distinguish statisticians from other ICT occupations. Hence, several machine learning techniques were used to assess those skills that best distinguish occupation codes from other job groups. After quality control and removal of duplications, the scraping collected more than 110,000 job advertisements: nearly 6,200 were classified as ICT or statistical positions (largely dominated by software developers). The data indicate that high‐level statisticians have superior and heterogeneous professional backgrounds, linked to theoretical statistics, where analytic skills are more relevant than computing skills. Many soft and management‐oriented skills were also called for, which are missing among lower level statisticians, who are restricted to more technical jobs oriented towards general computing and informatics.
Lovaglio et al. (Tue,) studied this question.