Publicis Sapient Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 29 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Publicis Sapient.
Publicis Sapient
Data Scientist Intern
Intern Average Positive experience Accept offer 2 rounds
Interview process
Technical screen Recruiter call
Interview formats
Technical Coding Behavioral
It was a two-round interview process. The first round involved a Senior Associate Data Science asking some NLP questions and then asking me to code Manhattan Distance and Euclidean distance between two n-dimensional points in Python. They also asked me to explain concepts like Tokenization and Accuracy measures. The second round was an HR round where I was asked to explain my resume projects and some standard HR questions about teamwork.
Confirmed questions2 questions
- Code the Manhattan and Euclidean distances between two n dimensional points in Python
- Tell me about your projects on your resume and your experiences working in a team.
Publicis Sapient
Senior Data Scientist
Senior Average Negative experience No offer 4 rounds
Interview process
Recruiter call Technical screen Take home Onsite
Interview formats
Coding Technical Presentation
The interview process began with an HR screening call. Following that, there was an online quiz consisting of 30 multiple-choice questions to be completed within 30 minutes. Next, a case study related to Data Science (POC) was given. The final stage was a one-on-one interview with the hiring manager, covering Data Science concepts, LeetCode problems, and a presentation of the case study.
Confirmed questions4 questions
- Can you introduce yourself?
- What are your thoughts on model deployment?
- Could you solve some coding problems?
Publicis Sapient
Data Scientist
Entry Average Positive experience Accept offer 3 rounds
Interview process
Recruiter call Technical screen Take home
Interview formats
Technical Coding Other
I got recruited on campus at IIT Hyderabad for a Data Science role. First, there was an online technical test. This test had multiple-choice questions (MCQs) and also coding questions. The MCQs covered topics like Python, Statistics, Machine Learning, Deep Learning, MLOps, NLP, Data Structures, and Algorithms. Then, there were two coding questions that were pretty easy and could only be solved using Python.
Confirmed questions7 questions
- Can you explain Bias and Variance and their connection to overfitting and underfitting?
- What assumptions are made for Linear and Logistic Regression Algorithms?
- What does Multicollinearity mean?
Publicis Sapient Data Scientist Interview Questions
Quoted word for word from Publicis Sapient interview reports.
“What is the distinction between precision and recall in Machine learning?”
Read reports →“Could you tell me why Linear Regression is not usually used for a classification problem?”
Read reports →“What assumptions are made for Linear and Logistic Regression Algorithms?”
Read reports →“Can you construct a SQL query using a group by clause?”
Read reports →“Can you explain Bias and Variance and their connection to overfitting and underfitting?”
Read report →“Could you explain what Support Vector Machines (SVMs) are and elaborate on the Kernel trick?”
Read report →“Could you design an efficient Python function to find real-time anomalies in a large time-series dataset?”
Read report →“Can you explain what regularization is and why it's important?”
Read report →“What is dimensionality reduction, and can you discuss PCA?”
Read report →Formats, difficulty and experience
Across all 29 Publicis Sapient interview reports.