Product: Imagine there’s an e-commerce website like Amazon that was launched two years ago, and they have been selling products meanwhile collecting reviews from those who have purchased the products in terms of the 1-5 stars and the text reviews. They have decided after two years to put the reviews that we have been collecting on the website and evaluate if they will improve the sales. They designed an A/B testing in which there are 50% control group and 50% treatment group. After they ran the test, they realized that the sales had dropped. What do you think caused the sales drop even though the reviews have been provided to the treatment group? Notes: • There is no novelty effect. • Both groups are completely randomized. • User experience has been the same meaning, there is no extra effort to place an order. • Those in the treatment group who have purchased products are more statistically satisfied than those in the control group. • Users have sorting and filtering options over the reviews.
Sr Data Scientist Interview Questions
3,513 sr data scientist interview questions shared by candidates
1st round: medium level data manipulation, wrangling 2nd round: probability, maths based coding, complex algorithm questions. 3rd round: Extremely vague system design. I was given computer vision based system design which I did 5 years back.
Derive MLE, Bayes theorem applied, confusion-matrix questions, classical test that detects well a rare disease and to calculate the risk of having that disease given tested positive
SQL medium-advanced, Pyspark, Python coding
Most of the technical interview was about the test assignment, there were also some general machine learning questions and a couple of things about testing your models and code
Joining multiple datasets to get to an answer
Focused on resume in general, not very technical at the time I interviewed.
All standard behavioral interview questions
1. General machine learning questions. 2. how would you identify X coming up in call transcripts.
Tell me one thing about yourself that would surprise me.
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