Browsing by Author "Yashchenko, L. O."

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    Data Analyst and Data Scientist Professions: Demand, Requirements, and Labor Market Prospects
    (Національна академія статистики, обліку та аудиту, 2026) Yashchenko, L. O.
    This article presents a comprehensive study of the current state, requirements, and development prospects of the data analyst and data scientist professions in the context of digital economic transformation and dynamic changes in the labor market. It is demonstrated that the rapid growth of data volumes, the proliferation of analytical platforms, and the active adoption of artificial intelligence and machine learning technologies are driving the increasing strategic importance of data professionals in managerial decision-making processes. The empirical basis of the study is laid by analysis of job vacancies on the Work.ua platform (March 2026), enabling to assess the structure of demand, the level of competition, the requirements to applicants, and the salary characteristics. The findings reveal a structural imbalance between labor demand and supply, shown in the higher number of applicants relative to available vacancies, as well as a gap between salary expectations and actual employer offers. The study systematizes the key competencies of data analysts and data scientists, including technical skills (SQL, Python, BI tools), analytical competencies (statistics, modeling), as well as communicational and managerial skills. It is demonstrated that the modern labor market increasingly demands multidisciplinary professionals capable of working across the full data lifecycle – from data collection to the implementation of business solutions. Special emphasis is placed on the transformation of professional roles, reflected in the blurring of boundaries between business analysts, data analysts, and data scientists, as well as the growing importance of hybrid positions. The analysis revealed a clear trend of transition from descriptive analytics to predictive and prescriptive analytics, significantly enhancing the strategic value of analytical activities. The practical significance of the research lies in potential applications of its findings in improving academic programs, developing professional standards, and setting human capital development strategies in the digital economy context.