As organizations collect ever-increasing amounts of data from more and more disparate sources, the demand for personnel with skills in data science continues to grow. Simultaneously, the field of data science is complex and has evolved over time, making it difficult for organizations to identify what job roles and associated skills they need to conduct data science successfully. This lack of clarity leads to the misconception that one person, the so-called data science unicorn, can do it all.  

The paper co-authored by Jonas Gunklach, Mario Nadj, Sven Michalczyk, Katharina Jacob, Christoph Gröger and Alexander Maedche offers clarity about the heterogeneous nature of job roles and skills required in data science by conducting a systematic literature review on job roles in data science. Second, we explore the proliferation and diffusion of data science over the past decade, tracing the shift from generalist Data Scientists to a landscape characterized by a variety of specialized roles. We draw on 16.348 unique job postings from established online job platforms and extract and characterize nine job roles along their skill sets. The paper offers a comprehensive, data-driven perspective on the roles and skills essential in data science. 

The paper is online available here:  https://link.springer.com/article/10.1007/s12599-025-00954-2