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Sr Data Scientist Interview Questions
3,513 sr data scientist interview questions shared by candidates
The first interview involved general data science questions that any average data scientist could easily answer. The data science questions in the second interview were also easy. The data scientist interviewing me from Sweden didn’t seem to know much about the field. It felt like a student interviewing someone at a professor level. However, I'll give their knowledge graph expert respect, as they were questioning my skills in this area well. The questions about knowledge graphs were about concepts on ontologies, OWL, and SHACL, which I had good experience with since they are part of my PhD thesis. The third interview questions were more about hiring, onboarding, salary, and a bit about my technical past experiences from the hiring manager. In the additional fourth interview, the lead in Oslo mentioned that he wasn't very good at coding. I thought he might be just being humble. He also said he came from a biology background, so I mentioned that was my weak spot and that I was learning to code genetic algorithms. He then admitted he didn’t know about that either. Unfortunately, this seems to be their level of expertise. His questions were just situational questions and cliche questions in management.
Need to classify (images or texts) into 4 classes. If we only have 1000 labeled samples, how can we use an LLM to get millions of labeled samples? How to do clustering? How to determine whether the resulting clusters are good?
Explain what the below pseudo-code is trying to do. array[N] # array of N integers, indexed 0 to N-1; # assume it’s populated with [1,4,2,-2,-9,10,2,12,2,-4,-4,-4,-4,2,6,7] peak = array[0] index = 0 output = [] # array of tuples For x in 1..N-1 if (array[x]*array[x-1] > 0) if peak < 0 and array[x] < peak peak = array[x] index = x if peak >= 0 and array[x] > peak peak = array[x] index = x else output.insert( (index, peak) ) peak = array[x] index = x end if end for return output
Explain one of your favorite Data Science projects.
Tell more about one bullet point on my resume
Talk about your research experience.
Les projets sur lesquels vous avez travaillé + Détail sur le travail pour un client.
Describe when did and how you use SAS/Alteryx in the past? What do you know Dataiku? How do you understand this software as a partner for a company?
Reviewed a data modeling question and wrote some SQL code.
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