Candidates applying for Data Science roles take an average of 8 days to get hired, when considering 8 user submitted interviews for this role. To compare, the hiring process at EXL Service overall takes an average of 14 days.
Common stages of the interview process at EXL Service as a Data Science according to 8 Glassdoor interviews include:
Skills test: 40%
One on one interview: 40%
Background check: 10%
Phone interview: 10%
Here are the most commonly searched roles for interview reports -
Say it is with hiring manager. Bombard with technical questions and expect people to answer everything. They go over most skill sets, so do be prepared to actually have to prove what you have written in skills. They take time to go over questions, and do give hints if you get stuck.
Interview questions [1]
Question 1
What do you use to analyze if a regression model is doing well.
I applied online. I interviewed at EXL Service (New Delhi) in Jan 2022
Interview
After getting shortlisted, had two technical rounds.
1) Basic python questions
2) SQL queries
3) 2 puzzles ,1 on time to calculate with two different sized rope and 2nd puzzle related to bulbs put in a dark room with switches outside,had to find defected one.
2nd technical round :-
Project explaination,be prepared for counter questions.
ML questions related to algorithm you chose or can be not as well because I diverted my interviewer to my strongest side of algorithm(tips).
Performance matrix use case related to recall precision.
Interview questions [1]
Question 1
Explain any project you have completed within the team or led by you?
I applied online. I interviewed at EXL Service (New Delhi) in Dec 2021
Interview
Total 3 Rounds
1. Technical Round:Focus on Technical Skill
2. Techno/Managerial Round: Focus on critical thinking/ able to solve problem/Probability and Statistics question
3. HR Round: Compensation Discussion
Technical round was good asked related question with resume and ML/DL deep questions.
Interview questions [1]
Question 1
1. Resume related
2. Clustering and Different types of clustering.
3.How to you compare two distribution - given col may be any type cat/continues,dictribution may be any
4. NLP related
5.Random Forest
6. Bagging vs Boosting
7.How you find correlation matrix between feature
8. How u handle imbalance dataset what approaches used for better model performance
9.Mathematical Question (10-12th Standard)