Bookmarking A methodology for agile data science by Edwin Thoen (ch.5 of Agile Data Science with R). Also favors Kanban. Highlights below.
As a rule of thumb, never work on more tasks simultaneously than the number of data scientists on the team.
One of the major pitfalls of trying to improve a data science product is endless exploration of a hypothesis.
How to manage exploration then?
The data scientist should not take longer for the task than the team agreed upfront, wrapping up even when he does not feel completely finished. If he found an alleyway that is still worthwhile exploring a new task should be put in the backlog, instead of persevering in the current task