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Data Scientist Interview Questions

In a data scientist interview, expect employers to ask questions that assess your data modeling, problem-solving, and programming skills. Be prepared to answer general questions that test your knowledge of statistics and data science. You should also be ready to answer open-ended questions that test your creativity, communication skills, and formal education in data modeling and programming.

Top Data Scientist Interview Questions & How to Answer

Question 1

Question #1: Which data modeling techniques do you prefer and why?

How to answer
How to answer: Turning data into understandable and actionable information is a critical part of the data scientist's job. This question allows employers to understand your data modeling skills and background. List and discuss your preferred data modeling techniques, including benefits such as ease of use, flexibility, etc.
Question 2

Question #2: How would you detect bogus Instagram accounts used for scamming consumers?

How to answer
How to answer: Questions like this one allow an employer to test your problem-solving skills. When answering open-ended questions such as these, feel free to ask clarifying questions and use whiteboards to demonstrate your coding and diagramming skills. Share your thought process as you work through the problem.
Question 3

Question #3: Describe circumstances that require a list, tuple, or set in Python.

How to answer
How to answer: Interviewers will use questions such as this one to test your Python programming skills. Review Python basics such as lists, tuples, and sets before your interview. You should be able to explain when and how each tool is used by data scientists.

54,396 data scientist interview questions shared by candidates

SQL A/B testing question: Q: You are tasked to analyze an experiment called thanksgiving-coupon. Instacart users in this experiment are randomly assigned to “incentive” group or “nonincentive” group. Users in the “incentives” group get an email with $10 off for their next order, and users in the “no incentives” group get an email reminding them to stock up groceries for the Thanksgiving weekend. The $10 off coupon expires on 11/29/2020 (Sunday) 11:59pm PST. How would you analyze this experiment? You have the table Experiments, which contains experiment assignments for Instacart users. Fields:
user_id
experiment: experiment name
group_ind: experiment group a user is assigned to
assigned_at_utc: assignment timestamp. You also have the Orders table, which contains all orders from a user. Fields:
user_id
 order_id
 order_created_timestamp_utc
 order_amount_usd You can use this code to convert time zones: order_created_timestamp_utc at time zone 'utc' at time zone 'pst' You also have the Coupon_spend table, which contains the redeemed thanksgiving-coupon for an order. Fields:
user_id
 order_id
 coupon_spend
avatar

Senior Data Scientist

Interviewed at Instacart

3.6★
Jan 13, 2022

SQL A/B testing question: Q: You are tasked to analyze an experiment called thanksgiving-coupon. Instacart users in this experiment are randomly assigned to “incentive” group or “nonincentive” group. Users in the “incentives” group get an email with $10 off for their next order, and users in the “no incentives” group get an email reminding them to stock up groceries for the Thanksgiving weekend. The $10 off coupon expires on 11/29/2020 (Sunday) 11:59pm PST. How would you analyze this experiment? You have the table Experiments, which contains experiment assignments for Instacart users. Fields:
user_id
experiment: experiment name
group_ind: experiment group a user is assigned to
assigned_at_utc: assignment timestamp. You also have the Orders table, which contains all orders from a user. Fields:
user_id
 order_id
 order_created_timestamp_utc
 order_amount_usd You can use this code to convert time zones: order_created_timestamp_utc at time zone 'utc' at time zone 'pst' You also have the Coupon_spend table, which contains the redeemed thanksgiving-coupon for an order. Fields:
user_id
 order_id
 coupon_spend

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