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<p>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. Hence, as one job role alone cannot cover the whole spectrum of data science, this article offers clarity about the heterogeneous nature of job roles and skills required in data science by first conducting a systematic literature review on job roles in data science. Underscoring the notion that data science has become a team sport, 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. In a second step, we draw on 16.348 unique job postings from established online job platforms and extract and characterize nine job roles along their skill sets. Our research offers a comprehensive, data-driven perspective on the roles and skills essential in data science, empowering organizations to effectively staff and conduct data science initiatives to derive value from data and maintain a competitive edge.</p>

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Beyond the Unicorn? Job Roles in Data Science

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月11日

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  • Jonas Gunklach,
  • Mario Nadj,
  • Sven Michalczyk,
  • Katharina Jacob,
  • Christoph Gröger,
  • Alexander Mädche

摘要

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. Hence, as one job role alone cannot cover the whole spectrum of data science, this article offers clarity about the heterogeneous nature of job roles and skills required in data science by first conducting a systematic literature review on job roles in data science. Underscoring the notion that data science has become a team sport, 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. In a second step, we draw on 16.348 unique job postings from established online job platforms and extract and characterize nine job roles along their skill sets. Our research offers a comprehensive, data-driven perspective on the roles and skills essential in data science, empowering organizations to effectively staff and conduct data science initiatives to derive value from data and maintain a competitive edge.