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ZS Data Science Associate Interview Questions and Answers
ZS Data Science Associate Interview Experiences
4 interviews found
Anonymous
Selected
I applied via Referral and was interviewed in Mar 2024. There were 3 interview rounds.
I was goven an assignment to work on - code the machine learning solution and present it in slides why I did it, how I did it, the rationale behind my steps and so on.
It was a technical discussion with questions from statistics, my previous projects and so on.
(2 Questions)
- Q1. It was general HR questions.
- Q2. General answers
Selected
I applied via campus placement at National Institute of Technology (NIT), Warangal and was interviewed before Apr 2023. There were 3 interview rounds.
Around 30 MCQs on the Aptitude test plus 2 basic coding questions.
(1 Question)
- Q1. I was asked to give a short presentation on any ML project I worked on and then follow-up questions
(4 Questions)
- Q1. Types of supervised learning problems.
- Ans.
Supervised learning problems involve predicting an output variable based on input data with labeled examples.
Classification: Predicting a categorical label (e.g. spam/not spam)
Regression: Predicting a continuous value (e.g. house prices)
Ranking: Predicting the order of a set of items (e.g. search engine results)
- Q2. Explain Logistic regression.
- Ans.
Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.
Logistic regression is used when the dependent variable is binary (0/1, True/False, Yes/No, etc.).
It estimates the probability that a given observation belongs to a particular category.
The output of logistic regression is a probability score between 0 and 1.
It uses the logistic functio...
- Q3. Explain Decision Trees.
- Ans.
Decision Trees are a popular machine learning algorithm used for classification and regression tasks.
Decision Trees are a tree-like structure where each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome.
They are easy to interpret and visualize, making them popular for exploratory data analysis.
Decision Trees can handle both numerical and c...
- Q4. Asked 2 puzzles from InterviewBit.
Interview Preparation Tips
- Machine Learning
- Python
Skills evaluated in this interview
Selected
I applied via campus placement at Delhi University - Hindu College and was interviewed before Apr 2023. There were 3 interview rounds.
A test of 10+ questions was conducted online- mostly mcq based but last question had a problem which needed to be solved via coding
(2 Questions)
- Q1. Showed data and asked what analysis can be made from this
- Q2. Asked about the features that can be build on particular healthcare data
(2 Questions)
- Q1. Asked questions about hobbies
- Q2. Strength and weaknesses
Interview Preparation Tips
I applied via campus placement at The LNM Institute of information Technology, Jaipur and was interviewed before Jun 2020. There was 1 interview round.
Interview Questionnaire
1 Question
- Q1. Basic data science questions
Interview Preparation Tips
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(2 Questions)
- Q1. What is bias v variance tradeoff
- Q2. When should bagging v boosting techniques be used
I applied via Recruitment Consulltant and was interviewed in Jun 2024. There was 1 interview round.
Video questions were asked and around 40 aptitude questions to solve within 12 minutes
Assignment was in word document , need to complete it and submit it post assessing it they will het back to us via mail
Selected
I applied via Naukri.com and was interviewed before Mar 2023. There were 2 interview rounds.
(1 Question)
- Q1. Questions were easy
Questions were easy, related to resume
I was interviewed before Feb 2021.
Round duration - 90 Minutes
Round difficulty - Medium
The test is divided into 3 sections:
1. R coding.
2. Python coding. This section includes NumPy and scikit questions.
3. Statistics. This section includes T-tests, Anova regression distributions, and chi-square.
Each section has roughly 12 questions. The number of questions and difficulty is not set in advance, the test is adaptive. The more correct answers you give, the more the questions get tougher. The qualification does not depend upon the number of questions solved, rather on the difficulty level you can achive.
(1 Question)
Round duration - 60 Minutes
Round difficulty - Hard
- Q1.
Rotate Matrix by 90 Degrees Problem Statement
Given a square matrix 'MATRIX' of non-negative integers, rotate the matrix by 90 degrees in an anti-clockwise direction using only constant extra space.
Inpu...
- Ans.
The task is to rotate a square matrix by 90 degrees in an anti-clockwise direction using constant extra space.
Iterate through each layer of the matrix from outer to inner
For each layer, perform a four-way swap of elements
Continue this process until all layers have been rotated
Round duration - 30 Minutes
Round difficulty - Medium
Interview Preparation Tips
Tip 1 : Have in-depth knowledge of data-frame manipulation using Pandas
Tip 2 : Learn all NumPy array methods
Tip 3 : Good working knowledge about Scikit Learn
Tip 1 : Have 2-3 good projects on Machine Learning or Data Science preferably in Python.
Tip 2 : List only those skills which you are good at.
Skills evaluated in this interview
(1 Question)
- Q1. Why Deloitte and why tax?
- Ans.
Deloitte offers a strong reputation, diverse client base, and opportunities for growth. Tax consulting allows me to apply data science to complex financial regulations.
Deloitte is a reputable company known for its diverse client base and opportunities for career advancement
Tax consulting offers the chance to work with complex financial regulations and apply data science techniques
Combining Deloitte's reputation with th...
(1 Question)
- Q1. What is the f1 score?
- Ans.
The F1 score is a measure of a model's accuracy that considers both the precision and recall of the model.
F1 score is the harmonic mean of precision and recall.
It ranges from 0 to 1, where 1 is the best possible F1 score.
F1 score is useful when you have uneven class distribution or when false positives and false negatives have different costs.
Formula: F1 = 2 * (precision * recall) / (precision + recall)
Skills evaluated in this interview
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ZS Data Science Associate Interview Process
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ZS Data Science Associate Reviews and Ratings
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Rating in categories
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