u/closer_2thetruth

My current duties involve more work on MS word. So it is a mismatch. Hehe I want to switch.

Quick background: I've spent 4 years doing end-to-end data work — building pipelines in Airflow, automating ETL by pulling from APIs, storing and transforming data, and finally visualizing it in Power BI and Tableau. Comfortable in the terminal, handle file ops daily. Basically, I own the full stack from raw data to the dashboard someone ignores in a meeting.

Here's my frustration: the actual technical work keeps getting buried under stakeholder opinions that have nothing to do with data. Non-tech people with zero context are increasingly shaping what I build and how. Worse, I'm seeing the field get flooded by folks who took a 3-month bootcamp and now call themselves "data analysts" — which is making the role feel increasingly commoditized and chaotic.

So I've been eyeing Data Science as a way to go deeper into tech and away from the noise. But I'll be honest — I haven't touched predictive modeling, ML pipelines, or anything involving serious stats implementation in code. I know about it but haven't built with it professionally.

My actual questions for this community:

Did any of you make this switch with a similar background? Was the grass actually greener or did the same stakeholder chaos just follow you?

Is DS genuinely more insulated from non-tech interference, or does it just swap dashboard clients for product managers who want "AI" slapped on everything?

For someone with strong engineering/pipeline skills but weak ML fundamentals — what's a realistic roadmap to bridge that gap while still employed?

Is this a legitimate career move or am I just burned out and romanticizing a field I don't fully understand yet?