This is a great story because it's not just about welding. I have seen many data science teams working under similar conditions: spending 90% of their time doin

This is a great story because it's not just about welding. I have seen many data science teams working under similar conditions: spending 90% of their time doing miscellaneous bullshit and 10% doing data science at best. Recall that data science itself is 80-90% data cleaning and basic exploratory analysis, so that means no more than 1-4% of their overall time is spent doing the work that they're actually trained to do, and that you are actually paying them to do. They look productive because they are always busy. But really they need helpers (data engineers and dev/data ops people) to do all the random software work, so the data scientists can actually build models, meet with senior leadership, and all the other actually value-generating work that justifies their high price tag, and moreover keeps them happy with the work so they are more likely to actually stay at your company.