Pros
Compensation slightly above average. Absolutely nothing apart from that.
Cons
Junk work, Poor management, No respect for employees. Joined this company thinking I would get to do impactful data science work. But the reality is nowhere close to that. You will be hired as a data scientist but given junk engineering/deployment work. The justification for that from the management is - "If you are designing a machine learning model it is your responsibility to see it is deployed into production". And that is not a straight forward process because there is no process of things work here. Everyone will invent their own process pushing thousands of junk code to production repositories which can break any day only to frustrate another ill-fated engineer who attempts to clean up this mess. End result you will end up wasting months doing junk engineering work, navigating through inconsistencies in dependencies. If something doesn't work in the dependencies you are having you are expected to fix that too. You are expected to work on-call for a system you have no idea what is going on. If something goes wrong you are responsible. The blame game is strong. There is no learning component to the job. You will build a basic version of some well-known models and get frustrated getting that to production.