Applied Scientist applicants have rated the interview process at Amazon with 3.2 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 80% positive. To compare, the company-average is 58.2% positive. This is according to Glassdoor user ratings.
Candidates applying for Applied Scientist roles take an average of 21 days to get hired, when considering 5 user submitted interviews for this role. To compare, the hiring process at Amazon overall takes an average of 31 days.
Common stages of the interview process at Amazon as a Applied Scientist according to 5 Glassdoor interviews include:
Skills test: 33%
Phone interview: 33%
One on one interview: 33%
Here are the most commonly searched roles for interview reports -
There were two tech rounds with the team members about the background, experiences and coding test, had a shadow in one of them. The next one will be a job talk but haven't made it there
Interview questions [1]
Question 1
what are the differences between cross-entropy loss and contrastive loss?
I applied online. The process took 4 weeks. I interviewed at Amazon (Bucarest, ) in Aug 2023
Interview
The Amazon Science Machine Learning interview evaluates candidates' expertise in machine learning, algorithms, and problem-solving. It includes technical assessments, coding challenges, and discussions on research projects. Emphasis is on both theoretical knowledge and practical application in the context of Amazon's scientific and ML projects.
Interview questions [1]
Question 1
- multiarmed bandits
- MLE vs bayes
- MLE for regressione how can we dot it
- A/B testing
- importance of randomization in A/B tests
- p-value
- bias/variance tradeoff
- quali modelli non c'è bisogno di trovare questo tradeoff (non-parametrici?)
- overfitting/capacity
typical process for a data science interview in tech: screen, take home, in person with five stations
one behavioral with a higher up, One coating in front of a laptop, and several q&a's with a applied scientist
Interview questions [1]
Question 1
how would you improve our existing model, after they described it