Senior Associate Scientist Interview Questions

157 senior associate scientist interview questions shared by candidates

I was directed to read several scientific papers (that they selected) to discuss during the interviews. This seemed strange as it's something I haven't encountered for an interview. I was also asked very basic technical questions about procedures and controls. The interviewers were all quite young and didn't seem able to adapt their interview questions to my experience.
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Associate Scientist/Sr. Research Associate

Interviewed at A-Alpha Bio

4
Mar 29, 2022

I was directed to read several scientific papers (that they selected) to discuss during the interviews. This seemed strange as it's something I haven't encountered for an interview. I was also asked very basic technical questions about procedures and controls. The interviewers were all quite young and didn't seem able to adapt their interview questions to my experience.

Assessement: Questions regarding sql, ML, stats , and 1 coding for ML and one for postsql 1st interview: Basics of ML, stats, python , sql like overfitting, vif, hyperparameter tuning, ar and ma model of time series and difference among them, gradient descent 2nd intervew: One aptitude, Architechture of LSTM, working of tanh gate, why data should be stationary for time series, one solving based on gradient descent, dropout.
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Senior Associate Data Scientist

Interviewed at Affine

3.6
Jul 12, 2024

Assessement: Questions regarding sql, ML, stats , and 1 coding for ML and one for postsql 1st interview: Basics of ML, stats, python , sql like overfitting, vif, hyperparameter tuning, ar and ma model of time series and difference among them, gradient descent 2nd intervew: One aptitude, Architechture of LSTM, working of tanh gate, why data should be stationary for time series, one solving based on gradient descent, dropout.

1) Technical difference between Pyspark and Pandas 2) If you have large dataset with 1000s of features and only want some important feature, how will you identify it? 3) Dimensionality reduction? And why PCA is not an ideal solution in real world? Any other options? 4) If you have to build a model for Business partners regarding calls received by them for Opening account, paying bill and q&a? How will you design the whole ML algorithm from scratch? What features you will consider as important? How will you get the data? All steps involved till end. 5) For continuous and categorical features, which ML algorithm is best? And why?
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Data Scientist Senior Associate

Interviewed at JPMorganChase

3.9
Apr 14, 2022

1) Technical difference between Pyspark and Pandas 2) If you have large dataset with 1000s of features and only want some important feature, how will you identify it? 3) Dimensionality reduction? And why PCA is not an ideal solution in real world? Any other options? 4) If you have to build a model for Business partners regarding calls received by them for Opening account, paying bill and q&a? How will you design the whole ML algorithm from scratch? What features you will consider as important? How will you get the data? All steps involved till end. 5) For continuous and categorical features, which ML algorithm is best? And why?

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