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I work for a large consulting firm that does both of these activities (data engineer/analyst delivering rapid value + long-term data scientist / architects engi

I work for a large consulting firm that does both of these activities (data engineer/analyst delivering rapid value + long-term data scientist / architects engineering fully integrated solutions connecting ML to business process) and I can say without a doubt we get much higher feedback from the the former than the latter. Most businesses think small. I'm not even sure it's about risk/reward, either. I think people really don't have vision especially when it comes to technology and more specifically data. The next generation is coming, though.

apohn 9y ago
IMO every Data Scientist needs to be able to quickly identify a win and deliver quick value, even in a longer term ML project. Iterate and get something out. Most people in large businesses cannot do any data ETL or build a dashboard, so if you can do that in the first few weeks of a project you've already got a deliverable/win. Having some expertise with BI applications (e.g. Tableau) has been a major strength for showing value.