Data Scientist applicants have rated the interview process at Equifax with 2.4 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 71% positive. To compare, the company-average is 59.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 26 days to get hired, when considering 7 user submitted interviews for this role. To compare, the hiring process at Equifax overall takes an average of 26 days.
Common stages of the interview process at Equifax as a Data Scientist according to 7 Glassdoor interviews include:
Phone interview: 23%
One on one interview: 23%
Group panel interview: 14%
Presentation: 9%
Background check: 9%
Skills test: 9%
Other: 5%
Personality test: 5%
Drug test: 5%
Here are the most commonly searched roles for interview reports -
Got the referral from a friend and got a phone interview a week later with the HR. Its quite easy and relaxed. HR told me that some one will call me next week
I applied through a recruiter. I interviewed at Equifax
Interview
3 interviews, one intro call with HR, one with hiring manager and teammate together and one with managers manager. It was overall an easy process which consisted mostly of explaining projects and experience
Interview questions [1]
Question 1
Give an example of how you’ve interacted with clients and problem solved
There were three rounds of interview, two tech plus one hr. tech revolved around sql, statistics, machine learning algos and its metrics. Focus on personal projects was also given. overall, the focus was on basics and how you would fit in the company
Interview questions [1]
Question 1
My projects and how my interests and skills align with equifax
I applied through college or university. The process took 1 week. I interviewed at Equifax
Interview
A short 30-minute interview covering behavioral questions and project/experience-related discussions. It may include challenges faced, problem-solving approaches, teamwork, leadership, technical contributions, key learnings, impact, collaboration, and adaptability in past roles or projects.