Round 1: Screening Round (On-Campus)
The first round was an aptitude-based screening test conducted on campus. It primarily consisted of:
Logical reasoning
Basic mathematics
Analytical problem-solving
The questions were designed to evaluate problem-solving ability and logical thinking rather than deep technical knowledge.
Round 2: Technical Assignment (AI/ML - Open Book)
In the second round, I was given an open-book problem related to AI/ML.
The task was to build a solution to detect fraudulent credit card transactions using machine learning algorithms.
It tested understanding of concepts like:
Classification problems
Data preprocessing
Model selection (e.g., Logistic Regression, Decision Trees, etc.)
This round focused more on approach and reasoning rather than memorization.
Round 3: Technical Interview (Deep Dive)
This was a discussion-based round focused on the previous assignment.
I was asked to explain:
My approach to solving the fraud detection problem
Choice of algorithms
How I handled data imbalance and evaluation metrics
Some additional questions were asked from:
Basic programming concepts
General technical knowledge
The goal was to assess depth of understanding and clarity of thought.
Round 4: HR Interview
The final round was with HR, which included:
Questions about background and experience
Career goals and motivations
Behavioral and situational questions
This round focused on communication skills, cultural fit, and overall personality.