KFintech Senior Data Engineer Interview Questions and Answers

Q1. It was a 1.5 hours if pure technical round based on python, shell scripting and SQL.
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Q1. Question on python and shell scripting but tough from 1st round
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Q1. This is will be techno managerial round and they will ask about project details ans technical questions on deep big data technologies.
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Q1. This is also same as 3rd round with tough questions.
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Q1. This was a round arranged specially for me for just rejecting purpose.
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1 hr test , basics C++, oops, pointers

Q1. Oops concepts , smart pointers, ask me write code of oops concepts and then cross questioning
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Q1. How can Logistic regression be applied for multiclasstext classification
Ans. 
Logistic regression can be applied for multiclasstext classification by using one-vs-rest or softmax approach.
• One-vs-rest approach: Train a binary logistic regression model for each class, treating it as the positive class and the rest as the negative class.

• Softmax approach: Use the softmax function to transform the output of the logistic regression into probabilities for each class.

• Evaluate the model using appropriate...read more
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Q1. What is tokenization in NLP? and, to get raw tokens for a sentence with words seperated by space, why use tokenizers from nltk instead of str.split()?
Ans. 
Tokenization in NLP is the process of breaking down text into smaller units called tokens.
• Tokenization is a fundamental step in NLP for text preprocessing.

• Tokens can be words, phrases, or even individual characters.

• Tokenization helps in preparing text data for further analysis or modeling.

• NLTK tokenizers provide additional functionalities like handling contractions, punctuation, etc.

• str.split() may not handle complex t...read more
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Q2. While tokenzing, if you want to not break some word pairs(or triplets), for ex, to not tokenize the words 'first' and 'name' when they occur together and consider them as a single token, how would you do i...read more
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Q3. For a data with 1000 samples and 700 dimensions, how would you find a line that best fits the data, to be able to extrapolate? this is not a supervised ML problem, there's no target. and how would you do i...read more
Ans. 
To find a line that best fits the data with 1000 samples and 700 dimensions, we can use linear regression.
• For unsupervised ML approach, we can use Principal Component Analysis (PCA) to reduce dimensions and then fit a line using linear regression.

• For supervised ML approach, we need to select a target column. We can choose any of the 700 dimensions as the target and treat it as a regression problem.

• Potential problems of...read more
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Q1. This round was entirely based on my projects on the resume!!!!
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Q2. Explain project starting from the business problem to the deployment? [I was being interrupted for clarifications and questions]
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Q3. [all of the follow up questions were baed on my answers] (some questions on businesss problem and rationale behing it, end users, how success will be measured and data collection that I can't disclose) a...read more
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Problem would be given to solve

Q1. Questions will be based on their the first round
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Q2. Questions will be from their projects
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Q1. Behavioral questions
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The first round was aptitude conducted through AMCAT. It had logical, verbal and quantitative aptitude (gamified aptitude round) and technical quiz. And the shortlists from this round had Automata coding test

The GD was for about 45 min and with two topics. The topic i got was "Is driverlesscar suitable for India? "

Q1. This was a purely technical round . Most of the questions were related to the projects from bachelors and masters
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Q1. There was a one on one coding round, where you were asked to write the programs and explain it to the panel.
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Q1. These were some usual questions like what are your plans for five years, where would you want to see yourself in 5 years , etc,...
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