If you truly wants to make impactful data science work, no matter the field, one thing you have to master early on is the ability to understand why your project exist.
I would say that, above even technical skills, this is the most important ability of a data scientist.
Spending time understanding clearly the motives behind the project, even if you are the one starting it, has three major benefit:
It Gives you Enough Context to Modify it 🗒️
In order to creatively re-shape the project with confidence as you gather more information about the data you need to understand the context.
I've never seen a research / data science project that went exactly as planned upfront. Projects either change incrementally, with big pivots or fails.
It Focus You on What Matters 🎯
Understanding why your project is relevant allows you to focus your limited time on the parts that truly matters. This knowledge will allow you to spend more time on the area that are impactful and less on out-of-scope ones.
This is key, because there is more things to improve in a project than resource available. Starting by improving the parts that have the highest ROI and then going down the priority list is a much better strategy than just randomly improving any parts.
It Enable You to Cancel the Project 🙅
It's a bit awkward to say, but a lot of data science projects I've seen shouldn't even have been started in the first place (I've been part of some).
At least not in their initial state. Ensuring that whatever you are working on is impactful for your stakeholders (including you) is the best use of your time.
Talk to your stakeholders, take notes and understand deeply why your project exist before writing any lines of code. It's a bit of a controversial take, but don't touch that keyboard until you understand the reasoning and that you agree with it.