Data Science: Profession and Education

Abstract

Advanced analytics, data science, and new generation artificial intelligence (Al) represent probably the most promising areas and directions in today's and near -future's Information and Communications Technology and Science, Engineering and Technology sectors and disciplines, where data science has become the major driving force of the new-generation Al. Data science and new-generation Al have attracted increasing interest from major governments, vendors, and academia, with important initiatives launched by major countries such as the United States,' China, and the European Commission. However, despite the fact that the role of data scientists has been described as the sexiest job in the 21st century, the qualifications and capabilities of a data scientist are not clearly defined; it is important yet undermined to define what makes the next-generation data scientists who can transform today's and future science, technology, innovation, and economy. On one hand, as an increasing number of data science courses are being created by online course offers and traditional institutions, data science has clearly formed a new profession. 8,°,1° On the other, high -end data science employers (including major innovators, vendors, and enterprises) complain the limited availability of qualified data scientists to enable their strategic development and foster their future competitive advantages. These disclose the deviated status of existing professional and educational markets, the restricted benchmarldng and accreditation of responsibilities and capabilities of data scientists, and the urgent need of standardizing and upgrading competencies and maturity of data science qualifications and education. This article intends to address these important issues, with an aim to contributing to the standardization and formalization of next -generation data science profession and education.