Sr Data Scientist Interview Questions

3,395 sr data scientist interview questions shared by candidates

1. Live coding: a. Create a list of 10 consecutive integers between 0 and 10 - Python b. based on the above list, print out odd numbers - Python c. Given a list of stores and products, derive a store-product summary table containing fraction of products for each store. (SQL) 2. Diff between supervised, unsupervised, reinforcement learning 3. What does p, d, q mean in Arima time series model? 4. If you have weekly sales and want to predict future sales, which time series models are you going to use? 5. how to deal with overfit 6. how to deal with outliers, any model to detect it 7. what is PCA 8. what is R squared, diff between r squared and adjusted r squared 9. what can you do to overcome multicollinearity 10. what is regularization, difference between Lasso and Ridge 11. How to deal with unbalanced binary classification 12. what you should do if a time series model is stationary
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Senior Data Scientist

Interviewed at Walmart

3.4
Oct 26, 2018

1. Live coding: a. Create a list of 10 consecutive integers between 0 and 10 - Python b. based on the above list, print out odd numbers - Python c. Given a list of stores and products, derive a store-product summary table containing fraction of products for each store. (SQL) 2. Diff between supervised, unsupervised, reinforcement learning 3. What does p, d, q mean in Arima time series model? 4. If you have weekly sales and want to predict future sales, which time series models are you going to use? 5. how to deal with overfit 6. how to deal with outliers, any model to detect it 7. what is PCA 8. what is R squared, diff between r squared and adjusted r squared 9. what can you do to overcome multicollinearity 10. what is regularization, difference between Lasso and Ridge 11. How to deal with unbalanced binary classification 12. what you should do if a time series model is stationary

The online screening is bit challenging covering from basic Data Science to Agentic AI concepts and two coding challenges Second was a case study was asked to make an AI application with open source LLM endpoints Third was supposed to be a tech interview on the case study but interviewer asked a seperate concept all to gether Confused and unfortunate experiene
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Senior Associate - Data Scientist, AI & Analytics

Interviewed at Publicis Sapient

3.4
May 26, 2026

The online screening is bit challenging covering from basic Data Science to Agentic AI concepts and two coding challenges Second was a case study was asked to make an AI application with open source LLM endpoints Third was supposed to be a tech interview on the case study but interviewer asked a seperate concept all to gether Confused and unfortunate experiene

I wasnt too prepared for the interview. I was asked questions on XGBoost, Logistic regression, some stat concepts, some drilling into NLP algorithms. Finally, there was a some drilling into web-visualization type questions using SVG etc. Overall, the questions werent super hard but I felt underprepared.
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Senior Data Scientist

Interviewed at Fidelity Investments

4.1
Aug 24, 2022

I wasnt too prepared for the interview. I was asked questions on XGBoost, Logistic regression, some stat concepts, some drilling into NLP algorithms. Finally, there was a some drilling into web-visualization type questions using SVG etc. Overall, the questions werent super hard but I felt underprepared.

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