It's probably not quite 10x. If I had to guess it's probably around 4x. This is because for every data scientist it helps to have at least one software engineer doing infrastructure (sometimes called a data engineer), at least one software engineer doing machine learning / productionization (sometimes called a machine learning engineer), and at least a handful of software engineers doing web page development, or app development, tied to the product the company is making. Usually data science works on developing a model to provide a feature for some software project, so quite a few software engineers are going to be necessary.

At startups, where the ratio of data scientists to software engineers is higher than at a large company, I tend to see on average 2 to 30 software engineers per data scientist, with 2 to 6 of them doing infrastructure.

There is the business analyst who may be sometimes called a data scientist, and they may work with less software engineers than a true blooded data scientist.