Data Science Analyst applicants have rated the interview process at Accenture with 3 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 68.4% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Science Analyst roles take an average of 22 days to get hired, when considering 7 user submitted interviews for this role. To compare, the hiring process at Accenture overall takes an average of 29 days.
Common stages of the interview process at Accenture as a Data Science Analyst according to 7 Glassdoor interviews include:
Phone interview: 31%
One on one interview: 23%
Background check: 15%
Presentation: 15%
IQ intelligence test: 8%
Drug test: 8%
Here are the most commonly searched roles for interview reports -
Campus Placement with one online test and three rounds of interview. Interview focus was on past projects, working of machine learning algo mentioned in the cv , python coding, behavioral questions.
Interview questions [1]
Question 1
write a code to import library for tree based model and also fit it on a dataset
Everyone I spoke with was very nice and helpful throughout the process. For me, it was not very clear based on the vacancy, in which team I would end up. Make sure to ask about the structure of Accenture and where you will end up, as the company is incredibly large.
Interview questions [1]
Question 1
In the first round with the recruiter I got questions like:
- Why do you want to join Accenture?
- Can you tell me a bit about your past experiences?
I applied through a staffing agency. The process took 3 weeks. I interviewed at Accenture (Bengaluru) in Feb 2024
Interview
The process took 3 weeks. First round was resume based. Discussion about projects and challenges faced. Second was a technical round based on Machine Learning and Python. Was informed about a third round, recruiter also called asking for feedback but didn't happen.
Interview questions [1]
Question 1
Scenario based question on Data and Machine Learning.