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In the introductory part of the article, the authors substantiate the relevance of developing methodological tools for analyzing job vacancies in the labor market in the context of the modern technological revolution, which significantly increases requirements for professional knowledge and experience of working personnel and changes the ratio between traditional and new professions.To assess the current situation on the labor market and the demand for currently existing professions, the main section of the published results of the study presents the algorithm for analyzing vacancies using large data arrays from open sources using mathematical and statistical tools and machine learning methods using the Python programming language and the IBM SPSS modeler analytical platform. The algorithm includes: parsing data on vacancies, analyzing vacancies by the main criteria, clustering vacancies by salary level and building a neural network model – a multilayer perceptron of the dependence of salary on a number of predictors. It should be noted that the developed algorithm is universal, because it can be used to analyze big data from any open source at a certain point in time.The results of the analysis will allow researchers and specialists of management structures to more realistically assess the current situation on the labor market, educational institutions will be able to adjust training programs in accordance with the modern requirements of employers, employers will make decisions on the development of competencies in their field of activity and conduct a comparative analysis of demanded vacancies in terms of quantitative and qualitative characteristics, and for the applicant it will be easier to see the demand for vacancies in the labor market and develop new skills.