Data Science doesn’t fit neatly into agile/software processes, but many are still valuable.
– Daily stand ups
– Planning, grooming, retro meetings
– Jira tickets
– Peer reviews
Adaptations we’ve made:
– 1 week sprints work better for us than 2 week sprints
– We rely heavily on timeboxing, because “definition of done” can be difficult at certain stages of the data science process
– We added a “design review” meeting to discuss DS approaches for active projects
– We don’t overthink estimation. We work to be directionally right, but focus most of our time on solving the problems in front of us.
If you’re re-thinking your Data Science process, start with familiar processes and then freely adapt them to your needs.
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