Pros
Pharma industry has been late to the digital innovation party, which means there is a lot of opportunity to drive meaningful change with automation and machine learning. AZ has also made real investment in data science-driven innovation, so tools (e.g., data science platforms) and data (internal, external) are becoming more widely available to data scientist project teams. In general, good work-life balance and great benefits.
Cons
Heavily regulated industry creates limited opportunity for rapid "test and learn" approach to creating and deploying ML models. Consensus driven culture tends to slow down decision making and innovation. Working on cross-functional teams across continents can make collaboration difficult (early Zoom calls). Finally, this is not unique to AZ, but there's always a risk that data science work can be outsourced, so political wrangling can hamper any ML project from the start.