Typical behavioral and deep dive in technical projects with questions focused on ML design.
Lead Data Scientist Interview Questions
409 lead data scientist interview questions shared by candidates
Tell me a situation when you cant not deliver the result on time and how to deal with it.
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?
asked about projects, frameworks used , how you manage team, casestudy without data
They will ask you to solve a assignment - a binary classification problem
Explain how do you design a ML system for information extraction from documents?
Regression and what features to choose for regressions.
Tell about your previous project
Questions générales sur les méthodes de ML que j'ai utilisées pour résoudre des problématiques : GNN, boosting, decision trees, etc.
Technical details about project, Transformers, LLMs, use case discussions
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