It seems like many of clients have hired and settled down their own data scientist teams and ecosystems. How can data science consultants survive? Where do we show our differences vs. their own ds team?

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Consultant DS have an edge by visiting multiple clients and keeping up to date with techniques, quality standards, and updated use cases. While in-house DS have a better work-life balance, they sacrifice work vatiety, and the ability to apply tech outside lf what was already built for their employer, often falling into more of a repair/maintenance DS. They also fail to keep up to date unless the job hop often, at that point are they really in-house?

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You have to actually do the work lol

My team runs circles around internal DS teams because we have the business knowledge AND the technical knowledge. Git gūd

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