Unicorn data scientist: the rarest of breeds

TLDR

Organizations seek “unicorn” data scientists—rare professionals skilled across mathematics, statistics, computer science, AI, and related fields. The study seeks to describe the authors’ pursuit of these elusive mythical data‑science unicorns. The authors conducted semi‑structured interviews with managers and directors from nine Australian government agencies to explore the concept. The study found no evidence of unicorn data scientists but identified six essential roles and their skill sets, and used the resulting framework to evaluate three Australian Master‑level data‑science programs, offering a theoretical tool for team composition and training. Findings may not generalize to smaller or less mature agencies and firms.

Abstract

Purpose Many organizations are seeking unicorn data scientists, that rarest of breeds that can do it all. They are said to be experts in many traditionally distinct disciplines, including mathematics, statistics, computer science, artificial intelligence, and more. The purpose of this paper is to describe authors’ pursuit of these elusive mythical creatures. Design/methodology/approach Qualitative data were collected through semi-structured interviews with managers/directors from nine Australian state and federal government agencies with relatively mature data science functions. Findings Although the authors failed to find evidence of unicorn data scientists, they are pleased to report on six key roles that are considered to be required for an effective data science team. Primary and secondary skills for each of the roles are identified and the resulting framework is then used to illustratively evaluate three data science Master-level degrees offered by Australian universities. Research limitations/implications Given that the findings presented in this paper have been based on a study with large government agencies with relatively mature data science functions, they may not be directly transferable to less mature, smaller, and less well-resourced agencies and firms. Originality/value The skills framework provides a theoretical contribution that may be applied in practice to evaluate and improve the composition of data science teams and related training programs.