EXL Service Data Scientist Interview Questions
& Process

The interview process and hiring went smoothly. The onboarding process was also good. Offer letters, background checks, and other paperwork were handled quickly. Basically, the whole recruitment trip from interviews to hiring to onboarding was smooth and nice for candidates. They made sure to communicate fast, have clear steps, and the onboarding was welcoming, helping new hires get settled in well.

I went through 3 rounds of interviews. The first was a technical round focusing on Machine Learning. The second round was also technical and included a case study. The final round was technical too, with two case studies. This last round was particularly challenging because the case studies were specific to their domain. I was rejected after the final round. I felt it was unfair to expect candidates to answer questions from a specialized domain.

For NLP roles, the process usually goes like this: First, we look at your resume to see if your experience and projects line up with NLP. Then, there's a quick chat to go over your background and skills, sometimes with a small coding or problem-solving task. After that, you'll have technical interviews which might include coding tests, and questions about data structures, algorithms, text processing, language models, and ML. We also check your understanding of NLP concepts and your past projects. Behavioral interviews are also part of it to see how you communicate and work with others, and how you solve problems. Sometimes, you might need to present an NLP project you've done to show your practical skills.