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Data scientists often collaborate with clients to analyze data to meet aclient's needs. What does the end-to-end workflow of a data scientist'scollaboration with clients look like throughout the lifetime of a project? Toinvestigate this question, we interviewed ten data scientists (5 female, 4male, 1 non-binary) in diverse roles across industry and academia. Wediscovered that they work with clients in a six-stage outer-loop workflow,which involves 1) laying groundwork by building trust before a project begins,2) orienting to the constraints of the client's environment, 3) collaborativelyframing the problem, 4) bridging the gap between data science and domainexpertise, 5) the inner loop of technical data analysis work, 6) counseling tohelp clients emotionally cope with analysis results. This novel outer-loopworkflow contributes to CSCW by expanding the notion of what collaborationmeans in data science beyond the widely-known inner-loop technical workflowstages of acquiring, cleaning, analyzing, modeling, and visualizing data. Weconclude by discussing the implications of our findings for data scienceeducation, parallels to design work, and unmet needs for tool development.

Orienting, Framing, Bridging, Magic, and Counseling: How Data Scientists Navigate the Outer Loop of Client Collaborations in Industry and Academia