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Skill-job mismatch is a prevalent and persistent phenomenon among highly skilled immigrants in the United States and around the world, but research on it remains largely insufficient in terms of theoretical framework and empirical analysis. This study examines skill-job mismatch among highly skilled immigrants in the United States. We proposed a comprehensive theoretical framework and tested it and the derived hypotheses using data from the pooled 2019-2023 American Community Surveys. The result shows that 36 percent of highly skilled immigrants experienced skill-job mismatch in the United States during the period under the study. Sequential logistic regression and multinomial logistic regression analyses reveal that human capital variables, many social capital variables, and structural inequalities in gender, race-ethnicity, region of origin, and spatial location have expected significant effects on skill-job mismatch, but assimilation variables display mixed effects. Human capital variables contribute most to the variance explained. The findings have significant implications for scholarly research and labor market policies.