- Who is an RSE, who is a data scientist?
- What does CI look like for data analysis scripts in Jupyter?
- Good data science working practices. What can we use from software engineering practices? What needs to be different? Are these just good reproducible research practices or something different?
- How do we generate test data sets that are minimal, but that we know provide full coverage of the problem space? Can we do this automatically? For all types of data?
- How to mirror academic RSE career development with non-academic practice? Is this possible/desirable?
- How/where to intervene to increase participation in data science by underrepresented groups?
- Can we identify/build a network graph to identify RSE career development – through the choice of different qualifications and work experience to jobs?
- How do we identify and support RSEs across a university, given they may not have an explicit RSE job title?
- What are the alternative training resources available for RSE development? E.g. moocs?