No questions, a SQl and Python take home test
Lead Data Scientist Interview Questions
351 lead data scientist interview questions shared by candidates
How would you convince a stake-holder (customer) on the business impact of the analytics solution you are providing him ?
What are your capabilties in SAS?
boosting algorithm, neural networks, pros and cons of different methods
Si tenía experiencia previa utilizando SQL. Si tenía experiencia previa utilizando AWS. Qué proyectos he participado de ML previamente y si he trabajado con clientes.
1st interview: got a relavitaly clean data set where I had to build a classifer (kaggle style) all done on local laptop. Juypter env.
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?
Questions were around my knowledge in DS product building, problem areas and general data interpretation.
Explain bias vs variance trade-off.
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