Pros
Good work-life fit, decent compensation.
Cons
I was hired as a Machine Learning Engineer, but ended up debugging and optimizing legacy ETL scripts with no data exploration, analysis, or opportunities to formulate business objectives that can be achieved through ML. This is because the Product Managers I was working with were working on the same product for 15 years. They believe that ML is just a bunch of buzz words with no potential to help the business. The managers do not like to be challenged to explore news ways of looking at their products' data to find out and fix loopholes. They rely on their domain understanding and make decision based on their "gut feeling" instead of being data driven. They need to adapt to machine learning thinking by gathering alternate data on their products, form hypotheses, come up with solutions to test them to improve their business rather than use ML at Hackathons just to demonstrate that they hire people who know ML.
