Nlp data scientist Interview Questions


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American Express
NLP Data Scientist was asked...6 January 2022

The first round questions included basic dataframe manipulations, a regex question on writing a pattern to identify specific phrase which could have any number of random words in between (eg. between high and calorie, there could be any number of words upto 4 eg. high word1 calorie, high word1 word2 calorie' etc). This also needed some basic preprocessings like handling unidecode errors, punctuations and numbers in a string. Another question was a probability based descriptive question and a easy question on coding to print numbers between 0 to 100 which were prime.

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The dataframe manipulations were basic pandas problems, the regex pattern could be solved by having a pattern like r"high\s((\w+)\s){0,4}calorie". Could not solve the probability one, and prime number one can be found anywhere on internet Less

hey this was your written test round only ....?? do you have ipython notebook ??? Less

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I won't divulge the custom questions they had because of an NDA. But I will divulge the interview questions that are carbon copy menial tasks. Of the first three phone/live-coding interviews, I was asked to do a merge sort. I guess I understand that they want to make sure I can code. But there's got to be a better problem. The many in-person interviews were (1) 1.5 hour coding-by-myself on a laptop, (2) describe a problem you worked on in detail, (3) "NLP" interview that didn't focus on NLP, instead they focused on AB testing (which is fine), (4) Lunch interview, (5) culture fit interview, (6) follow up/close/discussion interview. To be honest, I don't remember much near the end. I think I went directly home after and slept for 12 hours.

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Be honest, be yourself, and prepare!

My experience in Machine translation

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I did Machine translation using Hidden Markov Models

Thomson Reuters

What is wrong with Pandas?

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It is memory inefficient as it loads all the information (the whole table). So, it does not scale. Less

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Focus on information retrieval and search concepts, particularly as they pertain to the end user. I didn't get any standard algorithm or stats questions, but your mileage may vary.


Permutation of string; Sort array of strings

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List comprehension , Numpy Slicing , Dictionaries, Regression algo in python

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