LTIMindtree Data Scientist interview questions

I was invited to the LTI Mindtree Kolkata office for an in-person interview. The process was structured into two main rounds: 1. Automated Assessment (iBot) The first round was an automated assessment conducted via their internal platform (iBot). The test included basic multiple-choice and scenario-based questions, primarily focused on Generative AI concepts, including foundational understanding and recent advancements. 2. Technical Interview (In-person) The in-person interview consisted of the following segments: Resume-based Discussion: The interviewer started by asking questions from my resume. A major focus was on my Generative AI projects, for which I was asked to explain the architecture, technologies used, and the real-world impact or applicability. Core Machine Learning & Python: I was then asked some basic ML questions like algorithm selection, model evaluation, overfitting/underfitting concepts, etc. Python questions were mostly centered around logic, functions, and basic syntax – nothing too advanced. Design-based Scenario: One interesting part was a design question where I was asked: "How would you design an SQL bot that can take human language as input and return database query results?"

First Round – Online Assessment: The assessment primarily focused on Python and its libraries. There were also a few questions related to machine learning. Technical Round: This round began with an introduction, followed by a discussion of my machine learning and deep learning projects. Additionally, I was asked basic questions about Python libraries, along with some implementation-based queries. HR round:- basis HR question