The Different Types of Data Scientists

I've actually never thought of it this way, but I actually think you're spot on. While my background was much more on recommender systems, which are almost always external. These have a wide variety of problems that just don't exist in what we were calling internal problems. But as time has gone on, like, sure, we can ignore more things if we're building internal and external, if you're just based on scale. And yet, I feel like I've definitely seen teams where, for whatever reason, you know, they just get stuck in the tooling or the infrastructure of the platform.