The use of casual contract employment has become a prominent feature in higher education institutions worldwide, including the growth of adjunct roles in the United States and fixed-term teaching staff positions in the UK. In Australia, this trend has been a subject of significant controversy and national attention in recent years, as casual academic employees often fulfill core duties with less job security and remuneration than their ongoing counterparts. Concerns have been raised by policymakers, unions, and academic managers about the long-term ramifications of high levels of casualisation, including the potential impact on teaching quality, workforce sustainability, underpayment, and illegal work practices. A particular concern is the existence of a "precariat" -- academics seeking stable employment but finding only casual options, working close to full-time hours over many years. Despite the significance of casual employees in the Australian higher education workforce, there is a lack of systematic evidence on the prevalence of these "permanent casuals." This is due to the inconsistent data published by universities on the actual number of individual casual staff employed and their characteristics. To address this lack of granular and systematic analysis, this study examines academic casual employment at five universities during a single year (2021), aiming to understand the different patterns and characteristics of casual employment in Australian universities and determine whether there is a "typical" academic casual employee. The analysis of anonymised payroll data reveals that there is no dominant stereotype of a casual academic employee, but rather there are distinct patterns differentiating various types of academic staff members based on their characteristics. The key differentiator appears to be the number of years employed at a university, as well as the discipline in which academics undertake casual work. Age grouping and possession of a doctoral degree are less significant factors explaining differences in employment patterns within the sample.