The real issue with data science, from the perspective of ML pipelines/using ml in products, is most people are straight up not smart enough for it. The second the problem falls outside the bounds of a commonly used model, 90% of data scientists are ill equipped to come up with a profitable solution. So they stumble around in the dark, producing nothing of real value. People underestimate the degree to which extreme mathematical maturity and skill can bend the results of commonly used ml models.