1st interview: got a relavitaly clean data set where I had to build a classifer (kaggle style) all done on local laptop. Juypter env.
Lead Data Scientist Interview Questions
409 lead data scientist interview questions shared by candidates
The technical rounds and the case study were focused on traditional ML. How would you deal with columns containing hundreds of categories? How would you deal with class imbalance? How does xgboost deal with nan values? What is the difference between oversampling and class weights? What hyper-parameters did you use in your models? How did you decide between one hot encoding and target encoding? What was the loss function used and what the score function used and why they were chosen? Then there were questions regarding one of the projects you did and questions on that? Behavioural round - How would you deal with a low performer in your team? What challenges you have faced? What do you consider as failure? Hypothetical scenarios on linking your models to business KPIs ? How would you manage a project?
Sql question on cumsum ?
Find the diameter of Binary Tree?
Leadership, handling teams, expertise in tools, very basic and nonsense
Project discussion, basic statistics, basic ML. Questions revolved around your project and ML algos mentioned in the resume.
Quelles approches avez-vous eues l'occasion de tester pour l'implémentation d'un système RAG (Retrieval Augmented Generation)?
How would you gather data for traffic issues ?
What is Markov chain?
Are you female? if not you have a completely different bar.
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