Assessment and demand forecasting for IT specialists in Russia
Abstract. The digital transformation strategy implemented in Russia involves provision of all industries with IT specialists. The challenge of the study is benchmarking existing methodologies to quantify the demand for IT professionals. The purpose of the study is to develop and test indices to assess the demand for IT specialists and build predictive models. The research methods include aggregating data from government and corporate sources from 2015 to 2024, applying ETL processes to data processing, and building regression models. The Employment Index of IT graduates (hereinafter -ITV) and the Market Demand Index for graduates in IT areas of training (hereinafter -IRS) are proposed as key indica-tors. The Random Forest and Ridge regression models demonstrated high predictive ability (R2>0,82) for ITV and IRS. The hierarchy of socio-economic factors was identified that significantly affect ITV and IRS: for ITV - an increase in GDP (49%), the migration processes (37%), the state educational policy (14%); for IRS - migration (13%), the budget places in universities (12%), the demographic factor - the number of school graduates (10%). It was established that the maximum discrepancy in the values of the indices is observed in 2022, and then the situation stabilizes. The forecast for 2025 indicates the movement of the labor market in the category of IT specialists to a sustainable state, where graduation and employment of graduates is close to the number of vacancies in the labor market. The proposed methodology creates prerequisites for transition to management based on the data in planning the processes of staffing the Russian economy with IT specialists.
Keywords: labor market, IT specialists, forecasting, machine learning models, employment index, demand index.
Highlights:
- the approach to analyzing the demand for IT specialists in the Russian labor market was developed and substantiated on the basis of two indices: the IT Graduate Employment Index and the Market Demand Index. The proposed approach makes it possible to quantify the ratio between official statistical reportingdata and actual emerging labor market needs;
- it has been shown that achieving and maintaining a dynamic balance between the de-mand for statistical reportingdata and the demand for data on vacancies of IT specialists is a prerequisite for reducing labor market volatility and creating conditions for planning specialist training in vocational educational establishments;
- machine learning models based on the Random Forest and Ridge Regression frame-works with high prediction accuracy (R2>0,82) were trained and tested, that allows predicting the situation in the IT labor market for up to a year;
- the hierarchy of socio-economic factors has been established that affects significantly the values of the IT Graduate Employment Index and Market Demand Index and creates prerequisites for managing the situation in the Russian labor market in the category of IT specialists;
- the cyclical nature of imbalance in the Russian IT market was revealed with a recovery period of 2-3 years after the crisis.
Yuri V. Frolov, Timur M. Bosenko, Dmitry D. Zhavoronkov - Moscow City Pedagogical University, Moscow, Russia