Developer vs. Data Scientist (Guest on Data Science Deep Dive Podcast)

Why do conflicts often arise between Data Scientists and Developers? In this episode, my co-host Andy and I discussed together with Mira and Sebastian in the Data Science Deep Dive Podcast to get to the bottom of this question. We talk about typical clichés and why they lead to conflicts. Together, we discuss which skills help both species work together harmoniously in the end - instead of slowing each other down.

We cover various topics including clichés and conflicts, such as stereotypes about Data Scientists (Jupyter fans, PhDs) and Developers (perfectionism, black-box fear). We also delve into team organization, comparing cross-functional teams versus separate departments, and the pros and cons of each, including the agency model. Typical challenges like the handover of prototypes to development, understanding SLAs/response times, and database selection are also discussed. Finally, we explore the necessary skill set and collaboration, emphasizing the importance of generalist knowledge in DevOps and software architecture, as well as maintaining an open mindset.

Thanks to Mira and Sebastian at INWT for the invite.

Listen to the episode here.