Envié una solicitud electrónica. Acudí a una entrevista en Infosys en may 2024
Entrevista
Interview Scheduling takes longer?
Interview went good, questions asked were good as well.
Prepare well with SQL,python and resume project. Algorithms and SQL and practical knowledge of algo is required.
Preguntas de entrevista [1]
Pregunta 1
Explain XGBoost Algorithm
In the XGBoost you have 10-20 features how will it split features and calculate further ?
Worked on any cloud platform
what is Entropy
what is Information Gain
Hypothesis Testing
When to use precision and recall
What is Gradient Descent
what is Data Imbalance
What is SMOTE
Worked on Time Series
Tell me something about yourself
Why are you seraching job in India
Tell me about your recent project
Which performance metrics have you used in your project
Code analysis of Global variable in python
write query to find 5th largest salary in every department
Difference between union and union all
Difference between Delete and Truncate
What are window functions
Solicité el puesto a través de un captador. Acudí a una entrevista en Infosys (Bengaluru) en abr 2026
Entrevista
For Experience candidates it is some 2-3 rounds. On SQL questions come on Joins, Window functions and CTEs. On python and ML it would be error handling, data preprocessing, deployment and monitoring questions and a few behaviour questions
Solicité el puesto a través de un captador. Acudí a una entrevista en Infosys (Pune)
Entrevista
The interview process was well-structured and leaned heavily on practical application rather than abstract theory. It wasn’t a "LeetCode Hard" marathon; instead, the interviewers focused on how I write code in a real-world environment and how I think through architectural trade-offs.
Envié una solicitud electrónica. Acudí a una entrevista en Infosys (Bengaluru)
Entrevista
The interview itself was quite easy, to be honest, but the interviewer was rather rude and disrespectful at times. They asked questions about SQL and about the projects we had worked on previously. I also had to explain the procedures followed in a data science project.