That might be true for startups. But larger business organizations are far better of creating a specific heterogeneous team with data scientist, data engineer and ops in one. At least starting out. That way, there is inherent knowledge transfer. You are not artificially limiting your hiring pool and can actually get some T shaped folks being experts in a certain domain.

Later on you can then build more specific teams or even more cross functional ones.

Of course, if you only want feel the waters and check if DS use cases are viable at all, consider getting a (few) freelancers and but a somewhat technically inclined person in charge. If that's a success use it to get funding for a proper team.