Mobile device location data (MDLD) can offer a new perspective on measuring accessibility. Compared with the traditional accessibility measures, MDLD is capable of capturing people’s preferences with the observed locations. This study proposes a job accessibility measure based on the identified home and work locations from MDLD, evaluating the job accessibility by the proportion of workers identified working in zones within a certain time threshold. In the case study on the Baltimore region, the job accessibility from the MDLD-based measure is compared with the results from a widely-used traditional measure. Then, generalized additive models (GAM) are built to analyze the socio-demographic impact on job accessibility from a MDLD-based measure and a traditional measure, with a feature-to-feature comparison. Finally, the socio-demographic characteristics of regions where there are major disparities between the job accessibility from the traditional measure and the MDLD-based measure are also evaluated from the Student's t-test results.