With the development of the times, the competition in the future job market will become more and more intense. Therefore, how to use big data analysis methods to accurately predict the demand for occupational skills is of great significance. In this paper, Baidu search index from May 5, 2020 to December 31, 2024 is selected as the research data, and six influencing factors that are more important to the future demand for vocational skills in the job market are screened out as the explanatory variables of the empirical model. The random forest model was used to fit and predict the demand for vocational skills in the future job market, and finally, the PDP and SHAP value interpretable machine learning techniques were used to analyze the interpretable factors influencing the demand for vocational skills in the future job market. The results of the study show that the differences in core technical demand skills, communication skills, and the ability to apply interdisciplinary skills have the most significant impact on the model, with an average SHAP value of 0.102269, 0.032896, and 0.015822, respectively, which shows that the core professional technical demand has an important competitiveness in the future job market.
