I decided not to progress during the initial screening stage. I was directed toward a Data Analyst role where I would be expected to work for an unspecified amount of time before I could 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 productionizing ML models and software development.

Based on answers to my questions, the divide seems to be that you're either a data analyst working with SQL with occasional doses of Python and R, or you're a software engineer who handles everything from back-end development to machine learning applications.

In short, the above really speaks to the inexperience of recruiters and hiring teams, as they don't appear to understand the team functions mentioned above. Pooling everything 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 of all job functions, including software engineering.

What do you consider ML work?