Technical screen involved mainly SQL questions as this was for a data modeling focused role. Some on SQL logic (it's open ended, so you can answer with whatever dialect you're familiar with) and some on writing performant queries.
Staff Data Scientist Interview Questions
112 staff data scientist interview questions shared by candidates
The recruiter just asked some high-level questions about my past experience, and insisted that they were handing out take-home assignments to everyone when clearly it was false.
How would you do this statistical analysis task, calling it "AI". However, it was mentioned every Staff Data Scientist has left because there is no role definition and they still aren't sure what the objective of the role. You will be given a take home dataset of 1000 records and are only allowed 3 hours of working time including create a presentation for 15 minutes of interviews. In my case, I used libraries I had built to do RL hyper parameter optimization with XGBoost to use PDP plots to understand which variables impacted the target variable the most. Software engineers were the interviewers that only knew XKCD memes and didn't understand basic ML.
Tell me about your model deployment strategies.
Tell me about your experience. Go over past projects and say where you failed and where you succeeded.
How to measure model performances for classification models?
1) What is central limit theorem, how do you apply it in a simulation environment. 2) Limitations of Python programming language 3) How to evaluate accuracy of ML model and reduce complexity in terms of the number of features 4) How to perform dimensional reduction 5) Describe experience related to application of theoretical concepts to real-world problems. 6) Describe a project involving E2E DS process or lifecycle
What is your experience monitoring ml models in production
Python string manipulation, basic data structures. SQL build KPIs from a sample data
Leetcode medium coding questions. Both data structure and algorithms.
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