New report on career paths and prospects in US academic data science
A new report looks at the career paths and prospects of people working in academic data science in the US.
The survey and report are a joint collaboration between researchers at the Berkeley Institute for Data Science at UC-Berkeley, the eScience Institute at UW-Seattle, and the Center for Data Science at New York University.
The Moore-Sloan Data Science Environments survey spoke to 167 researchers who were affiliated with the three organisations, with respondents spanning many fields, roles, and career stages.
“Our motivation is to study how those who practice and support data- and computational-intensive research fit in the formal and informal organizational structures of academia. Our report discusses many issues around academic data science through the lens of career paths. We provide insights, recommendations, and questions for those practicing, supporting, or institutionalizing data science in academia,” the report authors say.
Many early career researchers are making substantial contributions to the research and teaching missions of universities, but are often not recognised or rewarded by traditional institutions.
“There can be substantial ambiguity and uncertainty among early career researchers about whether these kinds of contributions will pay off in their careers,” they say.
While graduate students, postdocs, and research staff with specialised data science expertise are often highly valued in more junior and support roles, long-term career paths are lacking.
However, there is no one-size-fits-all solution to creating fulfilling, sustainable career paths for academic data scientists, as respondents often had different career goals and priorities.