So, yes, I'm in agreement.
A data scientist is a researcher who answers a research question using data, and can lead the development of the research process. They may design the methods to acquire primary or secondary sources of data that inform the research process, monitor and ensure ethical responsibilities, curate the research data and results, or communicate the process and results to stakeholders. Coding is incidental to that process, and it is possible to be a data scientist without programming at all.
The openness to the truth of a research answer is what is often lacking in much of tech-driven data science. Mostly, it sounds more like a statistician who codes, than a researcher who focuses on data-as-source.
Anyhow, the first module is complete, and I still have the rest of the 20-module course outline - which was aimed at public health professionals - and was thinking of crowd-funding each module, if anyone is interested? It's based on the Sloyd model of teaching, so each module is discrete, building on the previous module, and provides a functional and holistic understanding of the scientific method as it applies to data.