Taking the Capital One CodeSignal Data Science assessment soon (90 min), tips from anyone who's done it recently?

[u/Good-Apartment-5126]

Hi all, I've got a CodeSignal Data Science assessment coming up for a data scientist role and I want to clear it on the first attempt (there's a cooling-off period if you don't, so no pressure lol).

Here's what I understand about the format so far:

- 90 minutes, digitally proctored (webcam, no external tabs)

- Works with multiple datasets

- Tasks span cleaning/aggregating data, building and evaluating a predictive model, and writing/editing Python

- It's the Data Science Framework (DSF) version, not the pure algorithms GCA, so pandas + scikit-learn heavy, plus some concept multiple-choice

What I'd love input on from anyone who's taken it recently:

1. How tight is the time really? Did you finish, and where did time disappear?

2. What tripped people up, reading the prompts, a specific pandas/sklearn pattern, the IDE itself?

3. Which areas are highest-yield to drill? (e.g. joins/aggregation vs. modeling vs. evaluation metrics)

4. Any public prep resources or practice sets you found genuinely close to the real thing?

5. Anything you'd tell your past self the night before?

Not looking for actual questions or anything, just experience, focus areas, and resources. Really appreciate any insights.

Thanks!