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Back end or front end?
Is data science over hyped and over saturated?
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Generally speaking, you will have a manager that will act as a gatekeeper for projects from leadership (ie discuss priorities, bandwidth of team, etc). You will then generally have a senior data scientist (more than one depending on the size of the team) who may or may not be the same seniority as their manager but they will be the ones who execute the project. Lastly, you may have some more junior staff to help with ad hock cleaning of data, simpler projects, etc.
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Another format is having an assortment of specialists who own projects individually and draw on the group for help as needed.
Deliberate group projects with several data scientists splitting the load also exist, though you can expect different people to take the lead at different project stages. This is based on the their availability and the main competency needed in a given stage--business, data, engineering, etc.
Some project will grow out of this once they reach production, with a single lead stabilizing as the core maintainer.
Having teams in different time zones also adds a layer of variation to how things run. In the case of off-shoring, you can expect a totally different dynamic between project owners and support staff v. what you'd see with everyone online at once and talking through the day.