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I think it depends on the company. In my experience most companies have it halfway between the things you described (some data engineering + some modeling). Com
by kajecounterhack 5y ago
I think it depends on the company. In my experience most companies have it halfway between the things you described (some data engineering + some modeling). Companies with less established infra generally have more data engineering work.
Imo unless you are a rich company or have a well funded research arm, it mostly seems wasteful to make someone's job pure modeling.
- disgruntledphd2 5y agoPure modelling teams are a pointless waste of space. It's entirely analogous to setting up an SQL team and then telling everyone else not to run queries. More generally, in order to provide useful solutions, you need some domain and data expertise, which tends to come from engaging with product, the business and the data. If you don't have that, you may as well replace your modelling team with a giant loop over the sklearn fit and predict API.