DATA SCIENTIST COMPETENCIES AND SKILL ASSESSMENT: A COMPREHENSIVE FRAMEWORK
Keywords:
Data Science, Competencies, Skills, Framework, Analytics, Knowledge, Learning, Adaptability, Multifaceted, Problem-solving, Industry, Trends, StrategicAbstract
In the dynamic Domain of data science, pivotal for data-driven decision-making, the role of data scientists has become crucial. These professionals extract insights from complex datasets, contributing significantly to business objectives. Beyond technical proficiency, their efficacy relies on a diverse set of competencies, vital for modern data analysis. This paper explores data scientist competencies, emphasizing the need for a structured approach to assess and develop skills. The multifaceted nature of data science is underscored, covering technical, analytical, and domain-specific proficiencies. The goal is to provide a comprehensive framework for professionals and organizations navigating this evolving domain. As organizations increasingly rely on data, this paper contributes to the understanding of competencies essential for success. The framework offers insights for individuals enhancing skills and organizations maximizing their data science teams' potential in today's data-centric era.
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