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Visa Inc. Data Scientist Interview Questions
& Process

Real candidates share what happened, how many rounds they had,
and how the experience turned out.

Based on 65 interview experiences · FREE TO READ

2.9 Rounds average
Average Typical difficulty
44.6% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at Visa Inc..

Showing 3 of 65
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Visa Inc.

Data Science Intern

Analytics · nearly a year ago

Intern Average Neutral experience No offer 3 rounds
Interview process
Take home Technical screen Onsite
Interview formats
Case Behavioral Technical

The final round for this internship involved three stages. It kicked off with a case study. Following that, there was a behavioral interview, covering standard questions you'd tackle using the STAR method. The last stage was the toughest, focusing on machine learning and statistics, so you really needed to grasp the fundamentals of stats.

Confirmed questions8 questions
  • Tell me about the case study question.
  • Can you describe the typical behavioral questions that can be answered with the STAR method?
  • What are your thoughts on machine learning questions?
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Visa Inc.

Data Scientist

Analytics · nearly a year ago

Senior Average Neutral experience Decline offer 4 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Technical Coding Case Behavioral Presentation

The steps of the interview process were pretty organized and it didn't feel like too much. However, the recruiter was kinda cold and didn't respond much. The main interview day was different than what was described; the ML part turned into a business case study, and the business case interviews were more of a discussion.

Confirmed questions6 questions
  • Technical questions for Python were of average difficulty.
  • Technical questions for SQL were of average difficulty.
  • The first section of the final interview was consulting, which was quick and generic. It was hard to see how one could prepare for it beyond using STAR stories from their resume.
Visa Inc. logo
Visa Inc.

Data Scientist

Analytics · nearly a year ago

Mid Easy Positive experience No offer 3 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Technical Coding Case Presentation Behavioral

Visa's Data Scientist interviews generally start with a recruiter screening, then move to technical coding challenges using Python or SQL. You'll also be tested on your knowledge of machine learning fundamentals, statistics, and modeling. Be prepared for case studies related to fraud, risk, or personalization, as well as exploratory data analysis and metrics. The onsite portion involves panel interviews where they'll assess your communication skills, ability to collaborate with stakeholders, business sense, how you design experiments, and your skills in presenting insights. They'll also ask behavioral questions to gauge culture fit and your expectations.

Confirmed questions1 question
  • How would you find the middle element in an array?

Visa Inc. Data Scientist Interview Questions

Quoted word for word from Visa Inc. interview reports.

How would you invert an integer without converting it to a string?

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What would be the difference in predictions between a linear regression run on an original dataset and one run on a dataset where every data point has been doubled?

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Can you write Python code using pandas to perform a group by operation?

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In SQL, how would you find the average price of the top 5 most expensive items in a dataset?

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Can you use logistic regression to create a classifier that predicts whether a customer will buy a product?

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How would you combine two tables, create a new column, and filter the results by date?

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What are some ways to assess how well a classification model performs?

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How would you create a new column based on a condition in the first column?

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Could you determine which of these decision boundaries could have been achieved by each of these classifiers?

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Formats, difficulty and experience

Across all 65 Visa Inc. interview reports.

Interview formats

Technical 35.1%
Behavioral 25%
Coding 23.8%
Case 10.1%
Presentation 5.4%

Interview difficulty

Easy 15.4%
Average 67.7%
Difficult 16.9%

Candidate experience

Neutral 33.8%
Positive 44.6%
Negative 21.5%