J'ai passé un entretien chez Publicis Sapient (Gurgaon, Haryana)
Entretien
The first round was online test then second round was interview based on resume and basic to advance machine learning questions and last round was hr h h h h h h h
J'ai postulé via une agence de recrutement. J'ai passé un entretien chez Publicis Sapient (Pune) en juin 2026
Entretien
I applied through a recruiter. Spoke with Hr regarding background and soon after first interview was scheduled for 1 hour. This interview went on for 1.5 hours though. They did a thorough check of the room i was in and also asked for id before the interview started. During the interview, the interviewer was extremely patient and polite. He started by asking about background and hobbies and went on to do a deeper technical dive in. He covered all the aspects of my resume starting from my first experience to my latest experience. Lot of ML questions, GenAI questions( as i had project mentioned in my resume), PowerBI(also from resume),Pyspark basics.
The interviewer was kind and patient enough to explain things that I didnt know and not get frustrated immediately if i answer incorrectly or am confused. I could answr most questions but thy wer looking mainly for GenAi role and I had limited knowledge regarding that.
Questions d'entretien [1]
Question 1
What is a transformer, pinecone, specific libraries for data cleaning?( genAI)
What is Clustering( ML)
Confusion matrix, precision, recall, confidence intervals
What is a dataframe, lazy evaluation,generator, decorator, Window functions, Yield vs return, Rownumber vs dense rank
Python DS question: given a list of lists , convert it to a single list
J'ai postulé via un recruteur. Le processus a pris 1 semaine. J'ai passé un entretien chez Publicis Sapient
Entretien
1. HR screening
2. Online quiz (30 MCQ in 30 mins time)
3. Data Science related case study (POC)
4. HM one on one interview (questions on DS concepts, leetcode problems and presentation of the case study
Questions d'entretien [1]
Question 1
1. Tell me about yourself
2. Questions on model deployment
3. Coding questions
4. Presentation of the DS case study and follow up questions