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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 -
It was the first round phone interview. The data scientist lead asked about my previous machine learning projects in detail(took about for an hour). It was a good experience overall.
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.