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    This study clarifies data science roles and work, identifying nine distinct data scientist profiles. It aims to guide visualization researchers toward impactful contributions in this evolving field.

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    Area of Science:

    • Computer and Information Science
    • Data Science
    • Human-Computer Interaction
    • Information Visualization

    Background:

    • Organizations increasingly rely on data science, yet its scope and practitioners remain ambiguous.
    • This ambiguity hinders visualization researchers in identifying impactful research directions.
    • A clear understanding of data science work and roles is needed.

    Purpose of the Study:

    • To provide a comprehensive model of data science work.
    • To categorize data scientists into distinct roles.
    • To inform visualization researchers about the landscape of data science.

    Main Methods:

    • Retrospective analysis of literature from data visualization, human-computer interaction, and data science fields.
    • Synthesis of findings into a comprehensive model of data science work.
    • Identification and breakdown of data scientists into nine distinct roles.

    Main Results:

    • A synthesized model detailing the scope of data science work.
    • Classification of data scientists into nine specific roles.
    • Analysis of visualization's role across data science tasks and varied tooling needs.

    Conclusions:

    • The study offers a concrete framework for understanding data science work and roles.
    • Findings empower visualization researchers to identify innovative opportunities.
    • This research aims to enhance the impact of visualization within the data science domain.