Position – Full-time Job
Profile – Data Science Associate
Process – CV shortlisting and Pre Placement Talk followed by an Aptitude test on HackerEarth platform then one Case study Interview round and finally the Technical interview round.
Result – Role offered
Online Aptitude Test on HackerEarth platform (1 hour 2 min)
The online test was split into MCQ and Programming. MCQ test had 42 questions focusing on fundamental concepts around Statistics, Data Interpretation, Logical, Data Science, and Machine learning. In the programming section, one had to solve a problem using any coding language.
Case De-Brief Round (Case Study Interview Round) (1 hour 20 min)
It was a live case study interview round via Zoom. The interviewer demonstrated the case study problem in a PowerPoint Presentation. This interview started with a brief introduction and then they jumped into the case study.
There is a practice of Chemotherapy treatment which is applied to cancer patients. Now some Pharma company is planning to introduce a new treatment named Immunotherapy to Stage 4 cancer patients.
- Do an EDA on the given data
- What will be the estimated pool of patients for Immunotherapy?
[The required data was also shown in the presentation in a tabular format ]
EBI + FIT (Technical Interview) (almost 1 hour)
- Walk me through your CV and share it on your zoom screen.
- A detailed discussion of my internship work.
- Question on the kind of data used?
- What are the models used for prediction along with their advantages and drawbacks?
- Discussion on the projects by mentioning the different ML algorithms used in it.
- What is your most comfortable ML model? (as I answered Linear Regression ) What are the assumptions of Linear regression?
- What do you understand by Conditional Probability?
- What is Bayes Theorem? They then asked a related problem. What are prior and posterior probabilities?
- What do you want to know about ZS Associates?
- The interviewers asked a real-life situation based question
Suppose a telecommunication company wants to estimate the number of their customers who will be switching to a different network in recent times, then frame what will be the necessary data required on their customers for the prediction and how will you do this prediction?
To know more about her experience of the interview at ZS Associates, feel free to reach out to Shreyashi on LinkedIn.
Cheers and Best!