Biodiversity loss is a major global challenge of the 21st century. Ultimately, extinctions of species are determined by birth and death rates; thus, conservation management of at-risk species is dependent on robust demographic data. In this study, data gathered from 381 (227 females, 154 males) long-finned pilot whales (Globicephala melas edwardii) that died in 14 stranding events on the New Zealand coast between 2006 and 2017 were used to construct the first age- and sex-specific life tables for the subspecies. Survivorship curves were fitted to these data using (1) a traditional maximum likelihood approach, and (2) Siler's competing-risk model. Life table construction and subsequent survival curves revealed distinct differences in the age- and sex-specific survival rates, with females outliving males. Both sexes revealed slightly elevated rates of mortality among the youngest age-classes (<2 years) with postweaning mortality rates decreasing and remaining relatively low until the average life expectancy is reached; 11.3 years for males and 14.7 years for females. Overall (total) mortality is estimated to be 8.8% and 6.8% per annum for males and females, respectively. The mortality curve resembles that of other large mammals, with high calf mortality, lower postweaning mortality, and an exponentially increasing risk of senescent mortality. An accelerated mortality rate was observed in mature females, in contrast to the closely related short-finned pilot whale (G. macrorhynchus), which selects for an extension to the postreproductive life span. The reason for the observed differences in the mortality rate acceleration and postreproductive life span between the two pilot whale species have not been established and warrant further investigation. Obtaining robust information on the life history of long-lived species is challenging, but essential to improve our understanding of population dynamics and help predict how future pressures may impact populations. This study illustrates how demographic data from cetacean stranding events can improve knowledge of species survival rates, thus providing essential information for conservation management.