Data Scientist applicants have rated the interview process at Deloitte with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 66.6% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 90 days to get hired, when considering 1 user submitted interviews for this role. To compare, the hiring process at Deloitte overall takes an average of 30 days.
Common stages of the interview process at Deloitte as a Data Scientist according to 1 Glassdoor interviews include:
Phone interview: 25%
One on one interview: 25%
Skills test: 25%
Group panel interview: 25%
Here are the most commonly searched roles for interview reports -
I applied through Deloitte Canada company website, then after about two weeks, recruiter send link for online assessment to be completed within 3 business days, include video HR screening and coding and one written questions
The interview was a part of the hiring program for the students graduating out of the Masters program. The interview and its process was carried out in a well planned manner.
I applied through other source. The process took 3 days. I interviewed at Deloitte (Bengaluru) in Aug 2020
Interview
It started with an online assessment which consisted of two programming questions.
After one day got a call from HR that the following day I will have my technical interview and she asked for my updated resume also. I had worked as a data scientist in my previous company for an year and prepared my resume like so. I was very excited as Deloitte is one of the best companies for data scientists.
Interview experience:-
Interviewer asked me to explain my previous work experience, he took some time to understand it well, From many skills in my resume he looked only two viz., Python and Tableau and asked me which one I was skilled in, I told him that I was more of an AI talent rather than being an expert of python or Tableau, so he could go in depth in Data Science and Machine Learning concepts. But I felt a prejudice in his questions as In Ai his questions were very- very basic and no brainer but hard in python, for example in Data science he was asking basic definition of dataframe and feature engineering but in python he asked about Metaclasses and design patterns and a lot more, some backend technologies like flask and Django, I kept explaining him that my expertise are in data science and machine learning but his 80-90 % questions were from python that too in depth. I think he was not an AI guy as he just asked 3 questions from data science and none from Machine Learning.