Competency-Based Role Modeling for Training Top IT Specialists
Abstract
Introduction. The digital transformation of society requires new approaches to the training of IT specialists. The Financial University under the Government of the Russian Federation is implementing a competency-based role model for the Applied Information Systems in Economics and Finance program, which combines fundamental training with individualized trajectories. Traditional models focus on a single specialization, but employers value versatility and adaptability.
Materials and Methods. The methodology is based on the analysis of professional standards, which are coordinated with the university's digital competence programs and the profiles of industrial partners. The methods of structural analysis, role matrix design, and financial modeling of interaction with the industry have been applied. Interviews have been conducted with company representatives regarding the requirements for competencies, the structuring of competencies into three key roles, the financial modeling of government grants and co-financing, the design of competency progression matrices by year of study, and the analysis of partner involvement forms.
Research Results. The program is based on three key roles: software engineer (development technology competencies), product manager (entrepreneurial thinking, product management), project manager (team organization, risk management). The progression of competencies is based on a four-year learning cycle. The financial model includes a government grant (70%) and industry co-financing (30%) annually. Partners participate in teaching, organize internships, and provide real projects and tools.
Discussion and Conclusion. The competency-based approach ensures the advanced development of competencies for digital leadership, fosters entrepreneurial thinking, and integrates social skills with technological knowledge. The co-financing model creates long-term motivation for partners to invest in the quality of education. The implementation results demonstrate the potential for scaling the approach to other areas.
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