I interviewed for a data scientist role at Hiscox insurance, after the introductory stage with the recruiter I had a technical interview that lasted for 45 mins to 1hr : This involved technical questions around data science like define type 1 error, type 11 error, where to use them, explain decision tree to a non technicals audience, explain gradient boosting, A member then look through my resume and asked random technical questions based on my resume. Next stage was coding interview: I discussed a ml notebook with the panel . Simple questions like .info, common exploratory data analysis functions , model evaluation metrics , final stage was a behavioural interview that asked different behavioural questions like how do you like explain technical terms to non technical audience etc
Interview questions [1]
Question 1
I interviewed for a data scientist role at Hiscox insurance, after the introductory stage with the recruiter I had a technical interview that lasted for 45 mins to 1hr : This involved technical questions around data science like define type 1 error, type 11 error, where to use them, explain decision tree to a non technicals audience, explain gradient boosting, A member then look through my resume and asked random technical questions based on my resume. Next stage was coding interview: I discussed a ml notebook with the panel . Simple questions like .info, common exploratory data analysis functions , model evaluation metrics , final stage was a behavioural interview that asked different behavioural questions like how do you like explain technical terms to non technical audience etc
Technical questions regarding classical data science and genai, such as how to evaluate models with umbalanced datasets. How to evaluate an llm based model. Don't know what would have been the other rounds
Asked technical Qs, open to ask Qs according to other open roles (such as Data Engineer) if the candidate preferred to be interviewed for the other role. The interviewees ( there were 2 ) were cool and nice.
Interview questions [1]
Question 1
Can you give an example of why you would increase and/or decrease bias?
