Abstract

In the context of fundamental changes in the economy and the labor market, the introduction of educational programs in the field of data analysis and machine learning at all levels of education with the priority of integrating mathematical, natural science and socio-humanitarian knowledge becomes important. An overview and analysis of foreign experience and main discussion topics in the development of educational modules for data science and machine learning for adolescents and adolescents is presented.

Abstract

In the age of digital transformation, there is an increasing discussion about human resource shortages. In particular, IT professionals, in general, specialists in science and technology (STEM - Science, Technology, Engineering and Mathematics). One of the decisive factors in attracting and retaining highly qualified employees is the level of remuneration, so it is important to understand what the determinants of its level in Russia are. Thus, our research answers the question: what factors influence the compensation of STEM professionals in Russia? The influence of human capital (special experience and availability of higher education) and institutional factors (organization size, economic sector, organization profile) were considered. The data of the National Research University Higher School of Economics Russian Monitoring of Economic Situation and Health for 2010-2020 were used for the analysis. The results show that the level of financial compensation increases when a STEM specialist has higher education, works in a large and commercial organization. Work experience has no effect on compensation. The profile of the organization (technical or not) also did not show an unambiguous result in this study.