ZS Associates Interview Questions

ZS Associates Interview Questions for a full-time job, by Arpan

Job Designation: Data Science Associate

Interview Questions
ZS Associates Interview Questions

Placement Process

Online Aptitude Test – conducted on Hacker-Earth/Hacker-Rank platform
  • The test was around 1 hour 15 mins
  • Questions were from basic statistics and machine learning algorithms like decision trees, random forests, etc. Most of the questions were conceptual.
  • There were some numerical aptitude and data interpretation questions which were also pretty basic.
  • In the end, there was a programming question of 20 points that could be attempted using any programming language like C, R, Python, Java, etc.

The above round was coupled with the CV selection round. Students who qualified the above went to the next round, i.e. Case Study Round.

Case Study Round
  • This round went for around 1.5 hours.
  • There were two interviewers in the zoom call scheduled.
  • They were presenting a case study of a drug to be launched in the market as an alternative to chemotherapy. A snippet of the data was displayed.
  • Questions were asked on what Exploratory Data Analysis (EDA) I would like to perform. 
  • What are the statistical tests like the Chi-square test, ANOVA, etc. used for? What is p-value and its interpretation? (These all came as counter questions to my answers). There were also comprehensive questions relating to sampling strategies used and where they may go wrong.
  • There were questions on which algorithms to be used for classification and regression. For linear regression, how can we determine the most important independent features?
  • Some questions were also asked on survival analysis and interpretation from graphs.

In a nutshell, they tested how you approach a data science problem and whether you are thinking the right way, along with basic statistical and machine learning questions. 

EBI + FIT Round:
  • This interview was with a very senior partner of the firm.
  • I had to explain my data science internship, the data-science projects I have done in detail and the hackathons I have participated in. There were a lot of discussions on why I chose a specific algorithm and why not the other, how correlation and causation are different, and how it affects the results. If I need to do something different in the modeling part, what it will be and why? If I am allowed to collect the data, how would I have done it?
  • Technical and also thought-based conceptual questions were asked.
  • Why do I want to join ZS Associates as a Data Science Associate?

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