Experian Data Scientist Interview Questions + Guide in 2024
Overview
Experian is a global leader in information services, empowering consumers and businesses to make confident data-driven decisions. Recognized by FORTUNE as one of the “100 Best Companies to Work For” and named among Forbes’ “100 Most Innovative Companies,” Experian is dedicated to innovation and excellence.
As a Data Scientist at Experian, your role involves researching and developing advanced machine learning solutions, prototyping new products, and evaluating data assets. You will also solve complex business challenges, present findings, and potentially work on cutting-edge AI projects, including Generative AI and large language models (LLM).
This guide will walk you through the interview process, commonly asked Experian data scientist interview questions, and tips to succeed. Let’s dive in!
What Is the Interview Process Like for a Data Scientist Role at Experian?
Recruiter/Hiring Manager Call Screening
If your CV is among the shortlisted few, a recruiter from the Experian Talent Acquisition Team will contact you and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.
Sometimes, the Experian data scientist 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 Virtual Interview
Successfully navigating the recruiter round will invite you to the technical screening round. Technical screening for the Experian data scientist role is usually conducted through virtual means, including video conference and screen sharing. Questions in this one-hour interview stage may revolve around Experian’s data systems, ETL pipelines, and SQL queries.
In the case of data scientist roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. In addition, your proficiency in hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.
Data science studies and similar real-scenario problems may also be assigned depending on the position’s seniority.
Onsite Interview Rounds
Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Experian office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.
If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the data scientist role at Experian.
What Questions Are Asked in an Experian Data Scientist Interview?
Typically, interviews at Experian vary by role and team, but commonly, data scientist interviews follow a fairly standardized process across these question topics.
1. Write a function combinational_dice_rolls to dump 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?
2. Create a function is_subsequence to determine if one string is a subsequence of another.
Given two strings, string1 and string2, write a function is_subsequence to find out if string1 is a subsequence of string2.
3. Write a function to return a list of all prime numbers up to N.
Given an integer N, write a function that returns a list of all of the prime numbers up to N. Return an empty list if there are no prime numbers less than or equal to N.
4. Create a function to add the frequency of each character in a string, excluding certain characters.
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.
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.
6. How would you explain what a p-value is to someone who is not technical?
Explain the concept of a p-value in simple terms to someone without a technical background.
7. What is the probability that a red marble was pulled from Bucket #1?
Given two buckets with different distributions of red and black marbles, calculate the probability that a red marble was pulled from Bucket #1.
8. 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 the probability that Amy wins by rolling a 6 before Brad.
9. 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 there are no prime numbers less than or equal to N, return an empty list.
10. How would you evaluate the suitability and performance of a decision tree model for predicting loan repayment?
You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate whether a decision tree is the correct model for this problem? If you proceed with the decision tree, how would you assess its performance before and after deployment?
11. What factors could have biased Jetco’s boarding time study results?
Jetco had the fastest average boarding times in a study. Identify potential biases in the study and what factors you would investigate to ensure the results are accurate.
12. How would you ensure data quality across different ETL platforms for PayPal’s Southern African survey data?
PayPal uses multiple ETL pipelines to connect data marts with survey platform data warehouses, including translation modules for text data. Describe how you would ensure data quality across these platforms.
13. How would you build a model to predict which merchants DoorDash should acquire in a new market?
As a data scientist at DoorDash, describe the steps you would take to build a predictive model for identifying potential merchants for acquisition when entering a new market.
14. How would you debug the marriage attribute marked ‘TRUE’ for all auto insurance clients?
You find that the marriage attribute is marked ‘TRUE’ for all auto insurance clients. Explain how you would debug this issue, what data you would examine, and how you would determine the actual marital status of the clients.
How to Prepare for an Experian Data Scientist Interview
You should plan to brush up on any technical skills and try as many practice data science interview questions and mock interviewsas possible. A few tips for acing your Experian interview include:
Know Your Algorithms: Experian questions often delve into algorithmic principles and their applications. Refresh your understanding of algorithms such as decision trees, SVMs, and neural networks.
Be Ready For Technical Specifics: Interviewers may inquire about advanced machine learning concepts and specific programming languages like Python. Be prepared to discuss eigenvalues, matrix factorization, and coding constructs like iterators and generators.
Master Data Manipulation: Highlight your skills in using data manipulation tools and performing data analysis. Knowing your way around SQL, Spark, and other data-processing technologies can set you apart.
FAQs
What is the average salary for a Data Scientist at Experian?
Average Base Salary
Average Total Compensation
What is the company culture like at Experian?
Experian fosters a supportive and innovative environment. Feedback from candidates highlights friendly and engaging interviewers, although experiences may vary. The company is proud of its recognition by Fortune and Forbes, celebrating diversity, inclusion, and continuous innovation.
Why should I choose to work at Experian?
Experian values the health and well-being of its employees with a flexible work schedule, a great work-life balance, and a range of benefits like competitive pay, generous vacation time, and more. Plus, you’ll be part of a company consistently recognized for its innovation and contribution to society.
Conclusion
As the technological landscape constantly progresses, the role of a data scientist at Experian offers a thrilling opportunity to make a substantial impact. Experian’s environment is crafted for growth and excellence with a blend of innovative projects involving Generative AI, a focus on machine learning, and a commitment to empowering consumers and businesses alike.
By preparing thoroughly on machine learning, programming, and data science basics, and aligning your skills with Experian’s values and missions, you can stand out and excel in your interviews.
Good luck with your interview!