Gender Factors of Graduates Hiring in IT Companies

This study examined whether there are gender differences among university graduates who began working in IT companies. The work was divided into two parts: theoretical and practical, with emphasis on the second. During the theoretical part, it was shown that the domestic IT market is developing, and the state is actively promoting this. Similarly, with the growth of enterprises, the consumption of information technology is also growing, which indicates the confident development of this area. Also, in the theoretical part, much attention was paid to the issue of the small number of women. Three theories were examined that identify the factors influencing the gender gap situation in the IT industry. In the practical part of this work, qualitative work with data was carried out: detailed descriptions of features were presented, both in quantitative and graphical representations. To select features, one of the machine learning methods was used - a decision tree, for which hyperparameters were automatically selected. During the regression analysis, additional processing of features was carried out. During the simulation, heteroscedasticity was discovered, which was subsequently taken into account when calculating the model results. The final model showed average quality, most features were statistically significant. Interpretations of the effect of the coefficients on the dependent variable were also presented. Thus, we can say that there is still a difference between graduates who got a job in an IT company, but without qualitative indications of how. During the modeling, the problem of heteroscedasticity was identified and it was not completely solved. There is an assumption that this is due to the signs themselves. For this reason, the continued development of research on this issue is based on the selection of other features. I also want to note that it was worth considering a larger data set, for example, taking into account all regions of Russia or considering data for several years.