In Silicon Valley back in 2014, when the seeds of ML/DS started to get traction, all the people with Data Science titles knew how to write Java webapps or Hadoo

In Silicon Valley back in 2014, when the seeds of ML/DS started to get traction, all the people with Data Science titles knew how to write Java webapps or Hadoop MR jobs to ingest, clean, transform, model/analyze, and serve results that went into production. The specialization def. has narrowed scope in the last ~10ish years, but the original roots were that: Java + stats + database knowhow. So yes, learn some production level skills. Having far too specialized people also runs the risk of lost-in-translation models that only work in the original implementation, until edge cases show up and model is out of date.