Technical test was a live, timed test where you could use any resources you needed to. It involved a series of short, straightforward Python tasks involving lists/dictionaries followed by a pandas data transformation task in a Google Colab notebook. Then I was asked to analyze a regression task output and any potential issues, followed by some general questions like, what are the pros/cons of random forests vs. gradient boosted forests; if you were trying to predict XYZ, what would you consider using, etc. Most of the other questions were around my past work or other case type questions - how would you solve this or go about doing this?

Questions were around my knowledge in DS product building, problem areas and general data interpretation.