Workforce Development in Genomic Data Science for Health: A Worldview

Abstract

Genomics has the potential to transform human health, biomedical research, and life sciences by providing deep insights into genetic variation and disease mechanisms. However, fully realizing these benefits requires a well-trained workforce equipped to handle, analyze, and interpret increasingly complex genomic and linked datasets. The rapid evolution of sequencing technologies, machine learning, and data science tools has heightened the demand for professionals proficient in bioinformatics, high-performance computing, and genomic data governance. This review presents a global perspective on workforce development in genomic data science, detailing key competencies necessary for both research and clinical applications. We discuss some of the existing training programs, competency frameworks, and regional approaches to skills development while identifying gaps in education, infrastructure, and accessibility. Additionally, we explore the integration of genomic data science into healthcare, addressing challenges such as equitable access to training and the need for cross-disciplinary expertise. Tackling these challenges is essential for cultivating a diverse, skilled workforce capable of driving advancements in genomic research, precision medicine, and public health.