The Senior in Data Science isn't about knowing more algorithms. It's knowing when to stop coding and start mapping.

Lately, l've been intentionally slowing down. As l've been upskilling and moving into more complex projects, l've hit a realization that's completely changed my workflow:
You can't fix a systems problem with a coding solution.

I used to think that if I could just write a cleaner function or tune a hyperparameter,I could solve any bottleneck. But I've come to understand that in the data space, everything is a web.

I'm learning to ask "System Questions" before I even open my IDE:

• Where does this data actually live before it hits my pipeline?
• If I change this feature, what silent impact does it have on the downstream users?
• Am I solving the root cause, or just patching a symptom of a larger architectural gap?

lt's been a bit of a humbling shift.It feels unproductive to spend two days staring at a whiteboard and zero minutes writing Python. But I'm finding that 1 hour of systems thinking saves me 10 hours of debugging a ghost in the machine later on.

l'm moving away from being a "Code First" builder to a "System First" thinker. It's a slower start, but the build feels so much more solid.
To anyone else upskilling right now: Have you hit that point where you realized the soft skills (like architecture and systems mapping) are actually the hardest part of the job?