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GEICO interviews FAQs
Data Scientist applicants have rated the interview process at GEICO with 3.3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 38% positive. To compare, the company-average is 48% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 29 days to get hired, when considering 16 user submitted interviews for this role. To compare, the hiring process at GEICO overall takes an average of 17 days.
Common stages of the interview process at GEICO as a Data Scientist according to 16 Glassdoor interviews include:
Phone interview: 31%
One on one interview: 21%
Presentation: 14%
Group panel interview: 10%
Skills test: 10%
Background check: 7%
Drug test: 3%
IQ intelligence test: 3%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 3 weeks. I interviewed at GEICO (Chevy Chase, MD) in Jul 2019
Interview
I applied online, a few days later HR contacted me to schedule a call with the hiring manager. It was an easy interview, covering my background and some standard technical questions.
Next round was a data challenge, which I had a week to finish. The data set seemed to be coming from real data they use. It was a classification problem. I spent some good amount of time on it and I believe I did a good job. I even had access to H2O and put the data there and the performance of H2O was only 2% better than my model while it found the same important features as I did. I made the presentation and submitted my code. A week later, I got an automated email that my application is rejected! Considering the amount of time I spent on the data challenge, I wish they had sent me a more personalized rejection email instead of an automatic one.
I don't know why they rejected me as I know my model was good. I found Logistic Regression to have the best performance so I guess they wanted a fancier model! Also, they probably got the same result as me in their own team and they were probably looking for someone who could get something better than the engineers they already have! So, I guess a pro tip would be if you use the classic methods and get a result, assume that they have already done this and you should make something that beats that.
Interview questions [1]
Question 1
Background question and standard technical question of a data science interview.
I applied through a recruiter. I interviewed at GEICO in Oct 2022
Interview
HR was very patient. The whole process was smooth and fast. 4 rounds of interviews in total. The first round was ML+resume; the second was python + SQL + easy algorithm, the third round was real case machine learning models, the last round was with one of the managers and asked resume and one machine learning model.
Interview questions [1]
Question 1
Asked many machine learning questions such as decision tree, random forest, KNN, and Kmeans. Must know the detail of each model very well. Deep understanding of your resume, asked many details
Onsite technical screen had SQL and python coding questions. Format was in a double spaced google doc, which is by far the worst possible way to ask these questions. Interviewer didnt seem to understand the problems during the interview leading to confusion. GEICO, like many financial or insurance companies, have really poor interview processes in place for data science. Bottom quartile compensation = bottom quartile talent.
It was a very strenuous and long process which required a lot of time spending through multiple rounds of interviews and take home exam. Many technical questions regarding ML from multiple interviewers.