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Despite occupying essential roles in healthcare, warehouses, and manufacturing, night shift workers remain underserved by transportation systems designed around standard daytime schedules. Using the Baltimore Metropolitan Area as a case study, this study provides an in-depth examination of night shift workers’ travel behavior and commute wellbeing. Survey data on commute choices, commute durations, travel costs, and perceived perspectives were collected from workers employed in night shift-based occupations. Structural equation modeling was then used to examine the relationships between travel behavior and perceived inconvenience by constructing a latent variable of commute burden. The results show that longer commute times and reliance on public transit are significant indicators of commute burden among this population. To further investigate why commute burden is associated with public transit, we conducted spatial visualizations and K-means clustering based on origin-destination nighttime trips derived from anonymized mobile phone data. Land use maps and nighttime public transit networks were referenced to identify travel flows and mobility patterns between high-flow zones, revealing the need to expand nighttime transit services in those areas. These findings reflect limited transit accessibility affecting night shift workers and offer actionable insights for nighttime transit planning and public service improvements in similar metropolitan contexts.