Top 10 Nielsen Data Scientist Interview Questions + Guide in 2025

Nielsen is a global audience measurement, data, and analytics leader, shaping the media and consumer industry. With a presence in over 100 countries, Nielsen provides insights into what consumers watch and buy, helping clients make informed decisions.

The Data Scientist role at Nielsen involves designing, executing, and delivering advanced analytics solutions. The position demands proficiency in Python, Pyspark, R, statistics, machine learning, and an understanding of analytics methodologies. Typically, the interview process includes five rounds: an HR interview, technical assessments, and discussions with hiring managers and senior leaders. Candidates should be well-prepared for Nielsen data scientist interview questions, covering past experiences, technical skills, and problem-solving abilities. Explore the interview guide on Interview Query to secure your dream job at Nielsen.

The interview process usually depends on the role and seniority; however, you can expect the following in a Neilsen data scientist interview:

Recruiter/Hiring Manager Call Screening

If your application is shortlisted, a recruiter from Nielsen will reach out to hold a preliminary screening call. During this call, they will verify your previous experiences and skill set. You may also encounter some behavioral questions during this phase.

The hiring manager might also be present during this screening to answer any questions you have about the role and the company. There could be surface-level technical discussions as well.

This recruiter call usually takes around 30 minutes.

Technical Virtual Interview

You’ll be invited for a technical virtual interview if you pass the recruiter screening. This stage typically includes a video conference and screen-sharing component and focuses on assessing your technical competencies. The interview will cover various topics, including Python programming, SQL queries, ETL pipelines, statistics, and machine learning.

You may also be given a take-home assignment that includes issues related to data analysis, visualization, and machine learning models to solve. Your solutions to these problems will be scrutinized during the interview.

Onsite Interview Rounds

If you successfully navigate the virtual technical interview, you will proceed to the onsite interview rounds, preceded by a follow-up call explaining the next steps. These rounds are comprehensive, including meetings with multiple team members across different levels. These interviews often assess your technical skills, as well as your problem-solving and analytical capabilities.

Sometimes, you must present your take-home assignments and explain your methods and findings during the onsite interview.

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

1. How would you ensure data quality across different ETL platforms for PayPal’s Southern African division?

PayPal partnered with a local survey platform for market research in Southern Africa. The data includes pre-quantified and text data in various languages. As a consulting engineer, you must ensure data quality across ETL pipelines connecting PayPal’s data marts, transactional data stores, and the survey platform’s data warehouses, including translation modules. How would you ensure the data quality?

2. How would you explain a p-value to someone who is not technical?

Explain the concept of a p-value in simple terms to someone without a technical background. Use analogies or everyday examples to make it understandable.

3. What is the probability that a red marble was pulled from Bucket #1?

You have two buckets with different distributions of red and black marbles. If a red marble is pulled, calculate the probability it came from Bucket #1.

4. What is the probability that Amy wins the game by rolling a “6” first?

Amy and Brad take turns rolling a fair six-sided die, with Amy starting first. Calculate Amy’s probability of winning by rolling a “6” before Brad does.

5. How would you write a function to return all prime numbers up to N?

Given an integer N, write a function that returns a list of all prime numbers up to N. If no prime numbers are less than or equal to N, return an empty list.

6. Create a function combinational_dice_rolls to list all possible combinations of dice rolls.

Given n dice each with m faces, write a function combinational_dice_rolls to dump all possible combinations of dice rolls. Bonus: Can you do it recursively?

7. Develop a function is_subsequence to check if one string is a subsequence of another.

Given two strings, string1 and string2, write a function is_subsequence to determine if string1 is a subsequence of string2.

8. Create a function to add frequency counts after each character in a string.

Given a string sentence, return the same string with an addendum after each character of the number of occurrences a character appeared in the sentence. Do not treat spaces as characters and exclude characters in the discard_list.

9. Write a function sorting to sort a list of strings in ascending alphabetical order from scratch.

Given a list of strings, write a function, sorting, to sort the list in ascending alphabetical order without using the built-in sorted function. Return the new sorted list rather than modify the list in place. Bonus: Aim for (O(n \log n)) complexity.

10. What is the difference between XGBoost and random forest algorithms, and when would you use one over the other?

Explain the key differences between XGBoost and random forest algorithms. Provide an example scenario where one algorithm would be preferred over the other.

To help you succeed in your Neilsen data scientist interviews, consider these tips based on interview experiences:

• Master Python and SQL: Nielsen places significant emphasis on Python and SQL skills. Ensure you are proficient and can handle coding challenges efficiently.
• Revise Statistics and ML Concepts: Be prepared for questions related to statistics and machine learning. Knowing concepts like precision, recall, bias-variance tradeoffs, and various ML algorithms will be beneficial.
• Prepare for Behavioral Questions: Behavioral questions are common. Practice providing structured answers that reflect your problem-solving skills and experiences with past projects.

What is the average salary for a Data Scientist at Nielsen?

What kind of technical skills are required for the Data Scientist position at Nielsen?

You should be proficient in Python, SQL, and R and understand statistics and machine learning. Familiarity with tools like Pandas and Pyspark and data visualization tools like Tableau or Google Data Studio will be beneficial.

What is the company culture like at Nielsen?

Nielsen fosters a growth-oriented culture where innovation and continuous improvement are highly valued. It’s an inclusive environment that encourages employees to explore new initiatives and methodologies, promoting personal and professional growth.

The interview process at Nielsen for the Data Scientist position includes multiple stages, generally encompassing HR screenings, technical evaluations, and managerial discussions.

If you want more insights about the company, check out our main Nielsen 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 Nielsen’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 Nielsen 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!