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During the past decades the importance of soft skills for labour marketoutcomes has grown substantially. This carries implications for labour marketinequality, since previous research shows that soft skills are not valuedequally across race and gender. This work explores the role of soft skills injob advertisements by drawing on methods from computational science as well ason theoretical and empirical insights from economics, sociology and psychology.We present a semi-automatic approach based on crowdsourcing and text mining forextracting a list of soft skills. We find that soft skills are a crucialcomponent of job ads, especially of low-paid jobs and jobs in female-dominatedprofessions. Our work shows that soft skills can serve as partial predictors ofthe gender composition in job categories and that not all soft skills receiveequal wage returns at the labour market. Especially "female" skills arefrequently associated with wage penalties. Our results expand the growingliterature on the association of soft skills on wage inequality and highlighttheir importance for occupational gender segregation at labour markets.

Responsible team players wanted: an analysis of soft skill requirements in job advertisements