Probability (Bayes' Rule, etc), statistics, algorithms, calculus.
Data Scientist Interview Questions
Data Scientist Interview Questions
In un colloquio per Data scientist, ti verranno poste domande volte a verificare le tue capacità di data modeling, risoluzione di problemi e programmazione. Preparati a rispondere a domande di carattere generale che valutano la tua conoscenza della statistica e della scienza dei dati. Dovresti inoltre prepararti a rispondere a domande aperte mirate a testare la tua creatività, le tue doti comunicative e la tua formazione nella programmazione e modellazione dei dati.
Domande tipiche dei colloqui per Data scientist e come rispondere
Domanda 1: Quali tecniche di data modeling preferisci e perché?
Domanda 2: Come rilevi gli account Instagram fasulli utilizzati per raggirare i consumatori?
Domanda 3: Descrivi quali circostanze richiedono una lista, una tupla o un set in Python.
54,277 data scientist interview questions shared by candidates
-Resume related questions - Process of building a predictive model
Dynamic programming/backward induction on a multi-stage decision making problem
Work through problems on the hackerrank site, it's good preparation
what is your salary expectation?
Describe your previous projects
Statistics - performance metrics, Why GBM, why not xgboost , Differences between GBM and xgboost Then bias, overfitting ,underfitting, Regularisation , Lasso regression( explain). ... Followed by extended questions
write a code in R/SQL: Given a table with three column, (id, category, value) and each id has 3 or less category (price, size, color). Now, how can I find those id's for which the value of two or more category matches to one another? For eg: ID1 (price 10, size M, color Red), ID2 (price 10, Size L, Color Red) , ID3 (price 15, size L, color Red) Then the output should be two rows: ID1 ID2 and ID2 ID3
- What is over-fitting? How do you avoid it? - What types of regularization do we have? Which one is simpler to use? L1 or L2? - Explain decision trees? What are different metrics to classify dataset? - What is bagging? - We have two models, one with 85% accuracy, one 82%. Which one do you pick? - What is p-value and how can we use it?
Assumption of Linear Regression, etc.
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