Info Edge Data Scientist Interview Questions
& Process

So I interviewed with InfoEdge and wanted to share my experience. It kicked off with an Online Assessment covering aptitude, basic ML/DL concepts, and a simple Python coding problem. I passed that, and my interview was set for Dec 2nd, 2025. Before the interview, they gave a presentation on potential topics. They said the first round would cover basic math/stats, then ML fundamentals, followed by resume/project questions. If I passed Round 1, there'd be a Python coding round for EDA/data handling, and then an HR round. My first technical round was all about fundamentals, asked directly and conceptually. Started with linear algebra basics, like matrix rank and invertibility. Then stats, asking about when the median is greater than the mean (skewness) and to explain the Central Limit Theorem simply. Then we talked ML: what it is, linear regression assumptions, and explaining KNN. The questions were straightforward, checking clarity and basic understanding, not deep theory. I didn't make it past Round 1, but it was a good, informative experience. The interview matched the PPT syllabus, highlighting areas like core math and stats for me to improve. Overall, the process was structured, transparent, focused on fundamentals, and gave a clear idea of how InfoEdge assesses candidates for ML roles.

It was a 4 round process. Round 1 had basic python, ML, and DL questions. Round 2 was about questions from my CV. Round 3 was a coding round where I had to code and solve a problem given a dataset and a problem statement. Round 4 was an HR round.

It was a 4 round process. The first round covered classical ML from basic to advanced. The second round delved into advanced ML and neural networks, with some basic questions on concepts like backpropagation and loss functions. The third round was a Python coding test focusing on pandas, numpy, and matplotlib. Finally, the fourth round was an HR interview.