Data Scientist applicants have rated the interview process at GM Financial with 2.8 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 55.6% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 28 days to get hired, when considering 6 user submitted interviews for this role. To compare, the hiring process at GM Financial overall takes an average of 22 days.
Common stages of the interview process at GM Financial as a Data Scientist according to 6 Glassdoor interviews include:
Skills test: 20%
Presentation: 20%
Phone interview: 20%
Background check: 10%
Personality test: 10%
Group panel interview: 10%
IQ intelligence test: 10%
Here are the most commonly searched roles for interview reports -
I applied online. I interviewed at GM Financial (Dallas, TX) in Apr 2020
Interview
First round with recruiter was very regular questions thwt took half an hour like describing your work were you are. Second round 4 people in the team were asking questions on the phone.
Interview questions [1]
Question 1
They asked some questions about Pandas, specifically: What is the code for removing duplicates from data. It has been a little while but if I remember correctly they also asked questions on Lasso and Ridge with details.
I applied through a recruiter. I interviewed at GM Financial (Fort Worth, TX) in Nov 2025
Interview
I got OA from GM Financial, which including Python, numerical, and logic three parts in SHL. All questions are multi-choice questions and The time is unlimited. I think it is not hard.
I applied online. The process took 5 weeks. I interviewed at GM Financial (Dallas, TX) in Apr 2022
Interview
I felt the interviewers were interested in knowing my experience and background. They asked me quite a lot of questions. The interview lasted 75 minutes. But I did not pass the interview.
Interview questions [1]
Question 1
Why do you like to work in the financial industry?