Pros
Comparatively high pay. Low stress environment. Friendly colleagues. While the interview is hard, once inside, it takes very little to shine.
Kontras
No meaningful data science or machine learning work to do. Important projects are outsourced to consultancies and you are left to clean the mess they leave behind. Decision making for the provision of ML solutions is done by MBA graduates, not technical experts. Dysfunctional processes within the AI space and a lack of clear direction. It seemed as if hey are trying to "ride the AI/ML wave" without high-level management personnel who understands what this entails. Some of the core AI leadership at the top does not know how to code, nor do they have a basic understanding of the systems and procedures that feed into data science solutions.. Most forums for technical dissemination within the wider group are reserved for discussions of basic statistical concepts. Poor communication, inefficient security systems in place, no data sharing infrastructure, lack of engineering support.