Attract scientists and software engineers across disciplines

Attract and retain data scientists and research software engineers across the breadth of scientific disciplines, notably through developing:

a. attractive career paths for data scientists and research software engineers within publicly funded research and innovation, including facilitation of transfers between scientific disciplines, as well as careers combined with private sector experience; and

b. recognition and reward of data management skills and software development skills as high value added to publicly funded research and innovation.

To attract and retain data scientists and research software engineers, the following strategies should be considered:

• Offer attractive career paths: Provide indefinite contracts, competitive compensation, and interesting, impactful tasks to prevent talent from leaving academia for industry roles.

• Improve working conditions: Create dynamic, collaborative environments using agile project management methods and emphasising cross-disciplinary teamwork with a clear purpose and societal impact.

• Support training and career transitions: Address the surplus of postdoctoral researchers by offering intensive training in research data management, enabling them to become domain-specific experts. Establish learning communities with data software and repository experts to foster collaboration and skill development.

• Build skills diversity: Teams should include expertise in subject matter, programming (e.g., Python, web programming), statistics, data curation, workflows, and legal/privacy aspects.

• Enhance recognition: Acknowledge and reward data scientists' contributions through promotions, career mobility, and recognition of their skills as integral to publicly funded research and innovation. Engage society, industry, and governments to increase awareness of science teams’ value and purpose.

Attracting and retaining data scientists and research software engineers faces several hurdles.

• Lack of appealing career structures, including indefinite contracts, competitive salaries, and clear advancement opportunities, makes academia less attractive compared to industry. The salary gap between academia and industry further exacerbates this challenge, limiting the ability to compete for top talent.

• There is insufficient recognition and reward for data management and software development skills, which are undervalued compared to traditional research outputs like publications. This requires a cultural and systemic shift to prioritize these contributions as integral to research.

• The lack of mechanisms to facilitate transitions across disciplines and between academia and the private sector hampers career mobility, leading to talent loss from the academic workforce.