Sr Data Scientist Interview Questions

3,367 sr data scientist interview questions shared by candidates

Given a table named employees which contains columns employee_id, last_name, first_name, salary, department and another table, employees_projects, with columns employee_id and project_id, with a query to select the top two employees alphabetically per project, where alphabetically means ordered by last_name and then first_name.
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Senior Data Scientist

Interviewed at Hinge

3.6
Sep 1, 2020

Given a table named employees which contains columns employee_id, last_name, first_name, salary, department and another table, employees_projects, with columns employee_id and project_id, with a query to select the top two employees alphabetically per project, where alphabetically means ordered by last_name and then first_name.

LeetCode "704. Binary Search". Given an array of integers nums which is sorted in ascending order, and an integer target, write a function to search target in nums. If target exists, then return its index. Otherwise, return -1. You must write an algorithm with O(log n) runtime complexity.
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Senior Data Scientist GENAI

Interviewed at Manulife

3.9
Apr 6, 2025

LeetCode "704. Binary Search". Given an array of integers nums which is sorted in ascending order, and an integer target, write a function to search target in nums. If target exists, then return its index. Otherwise, return -1. You must write an algorithm with O(log n) runtime complexity.

1. write a python code foo(x) where foo(4) =3 and foo(3)=4 2. How would you design a google calendar-like app. 3. Given a jupyter notebook, find what was done wrong. Try going over model assumptions, accurate metrics for imbalanced data etc... They give you the data in advance so try going over it and predict what they might ask about it
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Senior Data Scientist

Interviewed at Pendo

2.9
May 9, 2023

1. write a python code foo(x) where foo(4) =3 and foo(3)=4 2. How would you design a google calendar-like app. 3. Given a jupyter notebook, find what was done wrong. Try going over model assumptions, accurate metrics for imbalanced data etc... They give you the data in advance so try going over it and predict what they might ask about it

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