Candidatei-me online. O processo levou 2 meses. Fiz uma entrevista na empresa ZS Associates (New York, NY).
Entrevista
First round was a one way interview where i was asked about 5 questions like tell me about a time when 'XYZ'. Next round was with the HR(basic qualification questions including experience with certain tech stack). Next round was a one hour technical interview where i was first asked to explain a project of mine and then asked questions on it. Later on, i was also asked a few basic ML, Statistics, big data questions. After that i had a super day where i had 3 rounds- 1 behavioural style, a 2 hour technical data science case study(Kaggle styled) and just after that a 45 minute interview with tech lead explaining my approach and getting asked different questions on that.
Perguntas de entrevista [1]
Pergunta 1
Precision vs Recall, Type 1- type 2 error, assumptions of linear regression, why do we use big data, How use SVM for multiclass, how to deal with data imbalance, F statistic, F test, t test, Degree of freedom of linear regression model, Lasso vs ridge regression
Fiz uma entrevista na empresa ZS Associates (Mountain View, CA).
Entrevista
Had a few coding rounds and a live coding round followed by behavioral and Unstructured interview. The interview experience was bad and the interviewer were very rude and not respectful of time.
simple process, lots of product casing with chart and tables, need to do quick calculations, have a whole presentation set up, interviewer was nice but really need to prep for product casing
Perguntas de entrevista [1]
Pergunta 1
given this chart: derive insights -> whole presentation of healthcare data
Candidatei-me online. Fiz uma entrevista na empresa ZS Associates.
Entrevista
10 minute case overview, then 2 hour independent work time for the case study, then 45 minute interview. The interview portion went over my code from the case and a lot of conceptual questions about data science and statistics topics.
Perguntas de entrevista [1]
Pergunta 1
Why did you choose these models, and describe how they work internally.
