I applied through a recruiter. The process took 1+ week. I interviewed at Grainger (Chicago, IL) in Sep 2016
Interview
first round phone interview with the hiring manager, second round with a senior DS in the same group.
Feedback is that I totally not good at machine learning.....first time that someone saying this for a guy who has worked in this field for more than 4 years.
Interview questions [2]
Question 1
The Senior DS asked about PCA, I explained how to do it, and also you can use SVD to achieve PCA. Then he is lost and asked how does it related to PCA. Then I explained, and then he said that it is hard to understand from phone, and SVD could do PCA. Why then you need an explanation of how to use SVD in PCA then.
Then asked me about what is Java's class, and I explained to him, he said that even I did a small project I would give the right answer..... I think first, every one might have a different answer, and second, even I gave a wrong answer, you can correct it. But donot say something that make the candidates feel that you are insulting him! Totally shame.
Regular phone screening, asked about salary expectation, work authorization, experiance level of the required tools in the job description. Overall good experiance and nice interviewer who is respectful and on time.
Screen phone call then in person. Screen phone call then in person. Screen phone call then in person. Screen phone call then in person. Screen phone call then in person. Screen phone call then in person
I applied online. The process took 3 weeks. I interviewed at Grainger
Interview
Pleasant and smooth. 1 HR screening round. 1 hour highly technical telephonic round with the hiring manager. Then, on-site interview with team mates. The interview overall was very technical. They test you in your problem solving skills in data science and tons and tons of conceptual data science questions related to stats, probability, distributions, models, etc. It was more of an NLP focussed interview overall. I had very little experience with NLP so they adjusted the questions based on my skills. They check your GitHub profile. Having a strong profile makes the difference I guess.
Interview questions [1]
Question 1
Convolution, Pooling, Object Detection algorithms, Python specific questions, Duplicate a Dataframe without actually copying the entries, activation functions, and other basic Data Science questions which you can answer if you have done some ML projects. A lot of other questions as well.
