Publicis Sapient is a leading digital business transformation company that partners with global organizations to help them achieve their digital goals. The company specializes in leveraging advanced technology and data to create innovative solutions tailored to modern business challenges.

As a Data Scientist at Publicis Sapient, you will engage with cutting-edge technologies in machine learning, deep learning, and natural language processing (NLP). The interview process includes a technical assessment comprising of Python coding challenges and questions on statistics, machine learning, and data structures. You will also participate in behavioral interviews and case study evaluations to demonstrate your decision-making skills and technical expertise.

If you are aspiring to join Publicis Sapient as a Data Scientist, this guide is designed to navigate you through the interview process and provide insights into common question themes. Welcome to Interview Query, where we help you succeed in your career aspirations!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Publicis Sapient as a data scientist. Whether you were contacted by a recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from Publicis Sapient's Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Online Test

For on-campus recruitment or initial filtering, an online technical test will be conducted. This test typically consists of MCQs on topics such as Python, statistics, machine learning, deep learning, MLOPs, NLP, and data structures and algorithms. Additionally, there will be two easy-level coding questions which can only be answered in Python.

Technical Virtual Interview

Successfully navigating the recruiter round or the online test will present you with an invitation for the technical screening round. This usually involves a virtual interview conducted through video conference and screen sharing. The interview may include questions focused on:

• Basic and advanced machine learning concepts
• Bias and variance, and their relationship with overfitting and underfitting
• Assumptions behind linear and logistic regression algorithms
• Multicollinearity
• The suitability of linear regression for classification problems
• Differences between classification and clustering
• Algorithms and problem-solving, such as the unbound knapsack problem and group-by based SQL queries

This interview might also include discussion of personal projects listed on your CV, OOPS concepts, multithreading, and polymorphism.

Assessment Centre

The assessment centre may involve multiple stages, including a coding challenge and a reflective interview about the coding challenge. These sessions are designed to evaluate your decision-making process, problem-solving capabilities, and technical skills. You may also engage in behavioral interviews consisting of typical behavioral questions, small case-study-type questions, and questions about your strengths, weaknesses, and what you look for in the workforce.

Onsite Interview Rounds

The final stage is an onsite interview loop, which involves multiple interview rounds varying with the role. These interviews will evaluate your technical prowess, programming, and machine learning modeling capabilities. If you were assigned take-home exercises, a presentation round might also be part of the onsite interview.

Quick Tips For Publicis Sapient Data Scientist Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Publicis Sapient interview include:

• Highlight Your Technical Projects: Be thorough with projects on your resume. Interviewers often use these projects as a talking point, allowing you to drive the conversation based on your expertise.
• Solid OOPS and Multithreading Concepts: Being well-versed in object-oriented programming and multithreading will give you an edge. If you know Java in addition to Python, it's a significant plus.
• Behavioral Preparedness: Be prepared to discuss your strengths, weaknesses, and what you look for in a workplace. Familiarity with common behavioral questions will help you navigate this part smoothly.

Typically, interviews at Publicis Sapient vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test multiple changes in a sign-up funnel. For instance, they want to see if changing a button from red to blue and/or from the top to the bottom of the page will increase click-through rates. How would you set up this test?

• What metrics would you use to monitor the health of the Stack Overflow community? Given a table of Stack Overflow posts data, suggest three metrics to monitor the health of the community. Write the SQL queries for these metrics.

• How would you investigate the underperformance of the Calm meditation app in a new country? As the PM of the Calm meditation app, you launch the app in a new country but it isn't performing as well as expected. What would you investigate to find out why?

• How would you design a function to detect anomalies in a univariate dataset? If given a univariate dataset, how would you design a function to detect anomalies? What if the data is bivariate?

• How would you design a machine learning model to classify major health issues? You work as a machine learning engineer for a health insurance company. Design a machine learning model that, given a set of health features, classifies if an individual will undergo major health issues or not.

• What is the probability that a coin is double-headed after 10 heads in a row? A jar holds 1000 coins, 999 are fair and one is double-sided with two heads. Picking a coin at random, you toss it ten times and see 10 heads. What is the probability that the coin is double-headed and the probability that the next toss is also a head?

• What is the relationship between PCA and K-means clustering? Explain how Principal Component Analysis (PCA) and K-means clustering can be used together in data analysis. Describe the benefits and potential drawbacks of combining these techniques.

What is the average salary for a Data Scientist at Publicis sapient?

Q: What is the interview process for a Data Scientist position at Publicis Sapient?
The interview process typically includes an online technical test with MCQs and coding questions, followed by technical and behavioral interviews. Important topics include Python, Statistics, Machine Learning, Deep Learning, MLOps, NLP, Data Structures, and Algorithms.

Q: What kind of technical questions can I expect during the interview?
Expect questions on bias and variance, linear and logistic regression assumptions, multicollinearity, and differences between classification and clustering. You might also encounter coding challenges and ML project-oriented questions.

Q: What should I know about the behavioral interview at Publicis Sapient?
The behavioral interview usually consists of typical behavioral questions and a small case study. Be prepared to discuss your strengths, weaknesses, and the key attributes you seek in a workplace. Showcase your decision-making skills and how you handle situational challenges.

Q: Any tips for the technical test and coding challenges?
Be prepared to answer coding questions in Python and to demonstrate your knowledge of machine learning and data structures. Reviewing algorithms and practicing with platforms like Interview Query can be beneficial.

Q: How important are my previous projects and resume?
Your resume and projects are very important. Detailed knowledge of your past projects can drive the interview. Make sure not to lie on your resume and be thorough with any listed skills and experiences.

Interviewing for a Data Scientist position at Publicis Sapient is a multi-faceted journey that ranges from online technical tests and coding challenges to in-depth technical and behavioral interviews. Expect questions on Python, statistics, machine learning, deep learning, MLOps, NLP, and data structures. It's essential to be comfortable with questions about bias and variance, multicollinearity, linear and logistic regression, and more. Your projects and past experiences play a crucial role, paving the way for meaningful discussions and a greater chance to impress.

If you want more insights about the company, check out our main Publicis Sapient Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Publicis Sapient’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Publicis Sapient Data Scientist interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!