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This is a good list... for one type of data scientist - the type that has heavy involvement in product and business decisions. Other data scientists are basica
by beforeolives 5y ago
This is a good list... for one type of data scientist - the type that has heavy involvement in product and business decisions.
Other data scientists are basically software developers with a very specific domain, a third kind focus a lot more on research and many data science jobs are some blend of all of these things. My point is that the author mentions in the intro how data science is very broad and then continues to focus on what's only a subset of all data science jobs.
With that in mind, the list is actually spot on - it's just good to know that it isn't relevant to many data science jobs.
- ian-whitestone 5y agoAgree with you that not all of these things will apply to every DS role - particularly research heavy ones. But my hope is the vast majority will.
- mturmon 5y agoYep, some research-oriented DS people are (rightly) obsessed (correct word) with a particular family of techniques (variational inference! random forests! adversarial networks!) and work to find problems to apply that family to. They literally do pattern-match on their techniques with every new problem they encounter, and move on if it doesn't fit. A lot of the other of your distinctions do still apply to such people, like knowing where the data comes from, knowing when to stop, and adjusting the message to the audience. So, still a good list. Also, even the research DS people need to evolve their techniques over time.