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Bridging the demand and the offer in data science
Author(s) -
Belloum Adam S.Z.,
Koulouzis Spiros,
Wiktorski Tomasz,
Manieri Andrea
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5200
Subject(s) - bridging (networking) , computer science , data science , matching (statistics) , big data , scalability , service (business) , field (mathematics) , job market , data management , knowledge management , world wide web , marketing , business , engineering , data mining , database , work (physics) , mechanical engineering , computer network , statistics , mathematics , pure mathematics
Summary During the last several years, we have observed an exponential increase in the demand for Data Scientists in the job market. As a result, a number of trainings, courses, books, and university educational programs (both at undergraduate, graduate and postgraduate levels) have been labeled as “Big data” or “Data Science”; the fil‐rouge of each of them is the aim at forming people with the right competencies and skills to satisfy the business sector needs. In this paper, we report on some of the exercises done in analyzing current Data Science education offer and matching with the needs of the job markets to propose a scalable matching service, ie, COmpetencies ClassificatiOn (E‐CO‐2), based on Data Science techniques. The E‐CO‐2 service can help to extract relevant information from Data Science–related documents (course descriptions, job Ads, blogs, or papers), which enable the comparison of the demand and offer in the field of Data Science Education and HR management, ultimately helping to establish the profession of Data Scientist.