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      Research Scientist Interview

      Jan 21, 2020
      Anonymous employee
      Bengaluru
      Accepted offer
      Positive experience
      Easy interview

      Application

      I applied in-person. The process took 2 weeks. I interviewed at ZAPR Media Labs (Bengaluru) in Oct 2019

      Interview

      The whole process was made smooth and easy by both technical and HR team. Overall the Interview process consist of 4 rounds. Round 1 - Introduction (brief conversation to get an idea of my interest and current area of work going in Zapr) Round 2 - Technical (Key topics - Basics of Machine learning and Speech processing and my current work) Round 3 - Meet the founders (Face to Face interview with the ZAPR's CTO (Sajo Mathews) Round 4 - HR round

      Interview questions [5]

      Question 1

      How regularization is done in the Neural network? How does weight change after applying it?
      Answer question

      Question 2

      In stock market prediction, what kind of ML algorithm can be used, type of loss functions, and type of activation functions are used?
      Answer question

      Question 3

      Is it possible to do the PCA operation with Neural network? How does an Autoencoder work? What kind of loss functions are used?
      1 Answer

      Question 4

      Difference between Wasserstein loss vs L2 loss in the context of GAN?
      Answer question

      Question 5

      How with limited data or single reference sentence prosody transfer can be done in Tacotron or any other network?
      Answer question

      Other Research Scientist Interview Reviews for ZAPR Media Labs

      Research Scientist Interview

      Mar 4, 2021
      Anonymous Interview Candidate
      Bengaluru
      No offer
      Negative experience
      Average interview

      Application

      I applied through a staffing agency. The process took 4 weeks. I interviewed at ZAPR Media Labs (Bengaluru)

      Interview

      2 Rounds Technical 1 Round HR Technical Rounds are gone well. The interviews were keep on postponed. It took one month for 3 rounds Something went wrong in HR round, She asked some regular questions like reason for change and salary expectations. I explained my reasons and expectations. That’s it, she concluded and dropped my profile. I didn’t bother about dropping my profile, what made her to drop my profile I didn’t get. Rejecting in HR round is not wrong, rejecting in HR round by taking 1 month for technical rounds is wrong. If it salary she could have gone for negotiation. but she didn’t. I want to suggest one approach to all the companies, please take HR round first, you can drop the candidates who are failed in your psychology test, it saves lot if time for us employees. Next take the technical rounds last one more HR round only about salary negotiation, as this is based on performance. Please don’t think you understood everything about the person by asking some random psychological questions in HR round. HR mentioned one quote “when we try something new, prepare to accept the failure also”. I like the quote. but first please plan it properly before trying, don’t plan the way you scheduled the interviews. company has good ratings, I only might have got this experience, all the best.

      Interview questions [1]

      Question 1

      How system call works ?
      Answer question
      1

      Research Scientist Interview

      Mar 28, 2019
      Anonymous employee
      Bengaluru
      Accepted offer
      Positive experience
      Difficult interview

      Application

      I applied through an employee referral. The process took 2 weeks. I interviewed at ZAPR Media Labs (Bengaluru) in Dec 2018

      Interview

      Telephonic discussion was mostly technical with focus on machine learning and data preprocessing. I will focus mostly on the on-site interview as it reflects the experience better. On-site interview process is completely hands-on. I was given a dataset with a few days time limit to explore in my own time. In the interview I was assessed based not just on my exploration of the data but also on the improvements I can make on the models during the interview. The process is rewarding because you are constantly guided by the interviewer and the results are awesome. This is followed by an in-depth discussion on architecting a pipeline/data model for a hypothetical company, which can be from any domain. For example I was asked to build a taxi app from scratch discussing all the elements that go into the system, from data to algorithms. This process is again a discussion rather than a QnA session.

      Interview questions [1]

      Question 1

      All questions in the on-site interview were based on possible improvement to the models that I had built. and were from these topics. 1. Dimensionality reduction (followed by using it) 2. Train multiple models on the dataset judiciously 3. Selecting the ideal metric for the dataset 4. From scratch ensemble learning on the dataset with pre-prepared models 5. Architectural questions and discussions on taxi service 6. How will you use LSTM for analysing time-series data 7. Time-series analysis to find outliers and trends
      1 Answer