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Asesor Cientifico Interview Questions

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8,074 asesor cientifico interview questions shared by candidates

They focused on how I approach an open-ended business problem: defining the question, choosing appropriate data and models, validating assumptions, and clearly explaining insights and trade-offs to non-technical stakeholders.
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Data Scientist

Interviewed at McDonald's

3.6★
Feb 27, 2026

They focused on how I approach an open-ended business problem: defining the question, choosing appropriate data and models, validating assumptions, and clearly explaining insights and trade-offs to non-technical stakeholders.

- Tell me about a time where you have worked with group? - Tell me about a time where you took some key decisions which impacted larger group? Technical questions: - What is the difference between Mean Absolute Error and R- Square? Tell me which metric to depending on use-case? - How do you detect outliers? - What is the mathematical formulae for R-square? - What do we call/tell when model performs better on training data and not on test data? -Which are different types of evaluation metrics? What is F1 score? -Which metric is good to use with imbalanced data? What is Precision? -What is data leakage? - What do you when there are null or missing values in dataset? Python Interview: - What is difference between List, Tuple, Array? -What is difference between Pandas series and Dataframe? - What is join and merge? - What is pickling? - What are different types of python libraries? - Name one dataset with imbalanced data? How do you go ahead with model building? What are pros and cons? ** There were few python questions on strings, lambda functions, date functions.
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Data Scientist

Interviewed at Legal & General

3.8★
Jun 13, 2026

- Tell me about a time where you have worked with group? - Tell me about a time where you took some key decisions which impacted larger group? Technical questions: - What is the difference between Mean Absolute Error and R- Square? Tell me which metric to depending on use-case? - How do you detect outliers? - What is the mathematical formulae for R-square? - What do we call/tell when model performs better on training data and not on test data? -Which are different types of evaluation metrics? What is F1 score? -Which metric is good to use with imbalanced data? What is Precision? -What is data leakage? - What do you when there are null or missing values in dataset? Python Interview: - What is difference between List, Tuple, Array? -What is difference between Pandas series and Dataframe? - What is join and merge? - What is pickling? - What are different types of python libraries? - Name one dataset with imbalanced data? How do you go ahead with model building? What are pros and cons? ** There were few python questions on strings, lambda functions, date functions.

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