I found that "being technical" means different things to different people. In the software world people seem to be referred to as technical when they write sof

I found that "being technical" means different things to different people. In the software world people seem to be referred to as technical when they write software systems not as much as singular scripts. Data science is definitely technical but a lot of code work tends to happen in Jupyter notebooks or something similar. The main challenge is in understanding the ML/AI algorithms, the possible choices for your analyses that actually make sense for the problem, ... . Besides that, due to the AI hype, there are so many people in data science who don't know much about coding or software engineering. Therefore, helping these people might be profitable (or not).