This research paper explores Italian study programs in data science in order to verify if knowledge and skills developed during the universities’ path are fit with data scientist job demand. The issue is introduced considering the companies’ growing need to derive insights from data, and consequently, to search for a staff with analytical expertise, the so-called data scientists quite rare. Literature review is focused on the data scientist’s specific characteristics. According to the ideal profile, the data scientist should possess skills enabling the scientific collection, analysis and use of quantitative data in addition to managerial and communication skills, ensuring profitable interactions with decision-makers. The methodology introduces an innovative semi-automatic linguistic analysis of textual data, which enriches traditional statistical methods in text annotation and increasingly constitutes a key step to retrieve more and more precise information from large corpora. As results, the data scientist education in Italy is not widespread and the skills match highlights significant gaps between universities and companies in developing programming and software development skills. In conclusion, an intensive university-business cooperation in order to prepare future professionals, in line with technological trends and company requirements, could contribute to fill this gap, producing positive effects for the social and economic development.

How universities fill the talent gap: The data scientist in the Italian case

Maddalena della Volpe
;
Francesca Esposito.
2020

Abstract

This research paper explores Italian study programs in data science in order to verify if knowledge and skills developed during the universities’ path are fit with data scientist job demand. The issue is introduced considering the companies’ growing need to derive insights from data, and consequently, to search for a staff with analytical expertise, the so-called data scientists quite rare. Literature review is focused on the data scientist’s specific characteristics. According to the ideal profile, the data scientist should possess skills enabling the scientific collection, analysis and use of quantitative data in addition to managerial and communication skills, ensuring profitable interactions with decision-makers. The methodology introduces an innovative semi-automatic linguistic analysis of textual data, which enriches traditional statistical methods in text annotation and increasingly constitutes a key step to retrieve more and more precise information from large corpora. As results, the data scientist education in Italy is not widespread and the skills match highlights significant gaps between universities and companies in developing programming and software development skills. In conclusion, an intensive university-business cooperation in order to prepare future professionals, in line with technological trends and company requirements, could contribute to fill this gap, producing positive effects for the social and economic development.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4735425
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