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Lead Data Scientist Interview Questions
409 lead data scientist interview questions shared by candidates
Refactor this poorly written code implementing an algorithm already available in a thoroughly tested, efficient, and extremely widely adopted software package while pretending it doesn't exist.
talk about related projects, basic ml concepts
In first round questions on time series forecasting, optimization (GA) and basic data science questions. In second round interviewer went bit deep on above algorithms and checked coding skills. In final round, end to end data science life cycle, deploying models in production, knowledge on front end along with a business use case.
Concepts of Data Engineering along with Data Science
why accuracy is not a good metric? in what cases recall is a better metric? what is p-value? how is lgbm different from gbm, xgboost?
Should you be concerned with capping and flooring variables for a random forest model?
All about dealing with conflict, because they have a culture of conflict.
1. How is word transformers different from Sentence transformers. 2. Scenario based questions. 3. When to use F1 Score, Precision, Recall Score 4. Clustering before train test split or after train test split. 5. I was surprised on this question. Do SMOTE increase your test data sample size as well 6. Scaling - MinMax, Standard and Robust Scaler 7. When to use class weights and oversampling/Undersampling ( No one can get it right at the first time). I wont recommend for someone who has good experience in Data Science. In my decade of taking/giving data Science interviews, this has to be rated as my worst experience.
Forests, boosting, projects from CV.
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