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DS was always an overloaded title - speciation into various other titles is ultimately good and indicates a healthy and maturing ecosystem. You still need DS th
by PLenz 3y ago
DS was always an overloaded title - speciation into various other titles is ultimately good and indicates a healthy and maturing ecosystem. You still need DS though, in the multi-armed bandit that is your organization your real DS are your explore function - they figure out what to do. The other roles are exploit - they do it.
- nerdponx 3y agoI think this sells the position short. Data analyst explore, data scientists are to have enough skill and expertise to actually make something out of what they find. That might be an XGBoost model to deliver a monthly forecast, or it might be a setting up an automated decision process. However where I draw the line (and where I think most data scientists should draw the line) is actually putting that stuff into production code. Maybe they're good enough to write the prototype, but you need somebody else on hand to help with test coverage, make sure it meets performance requirements, triage bug reports, etc. if you make your data scientist responsible for that, they are going to spend all of their time doing that, instead of doing the things that they are actually trained to do and that you are paying them to do. This is true even if they are a perfectly competent software developer.