The process took 1 day. I interviewed at Loylty Rewardz Mngt (Mumbai)
Interview
3-4 rounds for fresher.
1. Written test (Easy logical Reasoning questions)
2. Interview guesstimates, logical questions
3. Interview data science concepts ML, AI concepts
4. HR round for background check
Interview questions [1]
Question 1
5 coin tossed at least one head
ML concepts: precision, recall, AUC etc
Neural networks basics
I applied online. The process took 2 days. I interviewed at Loylty Rewardz Mngt (Mumbai) in Dec 2021
Interview
There were 3 rounds = 2 Technical + 1 HR.
Process took 2 days. Both the technical rounds were scheduled on the same day. One with Data Science Manager and other with Data Science VP.
First round was schedules for half an hour but it got extended till 1 hour. Second round got completed within half an hour.
In the first round the questions related to your previous work, ML algorithms, SQL and python coding were asked. Also they asked the scenario based questions.
In the second round, small case study was given which was quite easy.
Interview questions [1]
Question 1
1. Explain working of XGBoost, their hyperparameters.
2. SQL coding questions like join and merge.
3. What is underfitting, overfitting and generalized model.
4. Explain confusion matrix, AUC.
I applied through a staffing agency. The process took 1 day. I interviewed at Loylty Rewardz Mngt (Mumbai) in Jun 2019
Interview
It was a day long process. they have directly called me for the face to face.
First round was written based on probability, statistics and data science.
no domain specific questions, after that HR said to wait for a week for results, haven't even asked for water.
worse interview experience in a while.
Interview questions [1]
Question 1
probability and statistics related basic questions
We appreciate you taking time to share the feedback. At the same regret the inconvenience caused to you. As a practice we do keep water bottles in all our meeting rooms and at the reception and also inform candidates about the duration of Data Science Challenge. We are taking your feedback and will be working on the areas wherein we missed delivering a great experience for you. Wish you all the best for your future.