Normal for mid-career Data Science role?
I have 10+ years of experience in the Data Science team of a large manufacturing company. My team builds ML (and now AI) solutions for other teams within the company to use. I work with 2 junior data scientists. I perform project planning and management, technical architecture of solutions, code reviews, some hands-on work to create full stack AI chat bots. I've also been asked to ensure the products we build are adopted by our internal customers. Often times these are solutions management deems necessary but the actual users don't care about or want to use. The Data Science team also has goals for X million $$ savings from these solutions, that don't align with any of the business teams' objectives. The Data Science management is also pushing to move faster and keep delivering features while at the same time meeting quality.
Is this normal, how is this done in your companies? What kind of goals are set and what's the team composition like.