1. Live coding: basic dataframe operations, regression model fitting, handling class imbalance in SVM (basic) 2. Resume Based: Basics of ML, ML Ops, OOPS 3. Technical Round 1: Resume based, very detailed questions on projects, simple case study (problem formulation and brain storming) 4. Technical Round 2: Basics of ML Algorithms, Technical workings of them 5. Case Study: Forecast demand for sales of a product for a national company with stores in different location (store level forecast) 6. Simple ML questions, 5 min case study
Sr Data Scientist Interview Questions
3,374 sr data scientist interview questions shared by candidates
General background questions, education, practical experience, what I wanted in terms of career long-term, etc...
Went into a fair amount of expert knowledge on the domain and my experiences therein
My Experience level and what interested me about the Company
Describe the difference between various bagging and boosting methods in terms of bias and variance trade-off
hashmap question, two sum variant, ML theory questions
I was tasked with building a forecasting model for delivery times and explaining it,
Can you explain Gradient descent
How would you handle missing values?
Stats and Core Data Science Questions along with banking domain
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