Marvelous MLOps #20: Technical roles in Data?Science

As data has become a formidable asset, the main driver of innovation and growth, companies started to transform their teams towards being more data-driven. With that, a diverse range of roles emerged and started to work collaboratively to unlock the power of data, in literally every domain. Because in every domain, there exists data.

Who is doing what” is a question that can be answered differently depending on which organization you are referring to. In this article, we’ll try to outline the most common distribution of technical roles within ML. Please note that these definitions for each role are not rigidly fixed. What truly matters is understanding the duties and assignments associated with each role, rather than the specific title assigned to an individual. In some organizations, the roles below might be combined into a single role, or the other way around, split into multiple roles.

Read further here: https://open.substack.com/pub/marvelousmlops/p/technical-roles-in-data-science-who?r=w50g&utm_campaign=post&utm_medium=web