Decided to not progress during initial screening stage as I was directed toward a Data Analyst role where I would be expected to work for an unspecified amount of time before I can consider moving to ML roles, even though I already have prior ML and data science experience. Recruiters don't seem to understand the difference between insight analytics, predictive analytics and ML engineering. They also don't seem to understand the difference between productionising ML models and software development. Based on answers to my questions, the divide seems to be you're either a data analyst working sql with occasional doses of Python and R, or you're a software engineer who handles everything back-end dev to machine learning applications. In short, the above really speaks to the inexperience of recruiters and also the hiring teams as they don't appear to understand the team functions mentioned above. Pooling everything that is deemed too "advanced" for a data analyst who works mostly on SQL, toward the role of software engineers, doesn't make your firm the next Google. In fact, it does the opposite, by showing candidates how little you understand all job functions including software engineering.