Meta (Facebook) Research Scientist Interview Questions + Guide in 2024

Meta, formerly known as Facebook, is a global leader in social technology. Since its inception in 2004, Meta has continuously revolutionized how people connect and engage with the world through platforms like Messenger, Instagram, and WhatsApp. Currently, Meta is pioneering the next evolution in social technology through immersive augmented and virtual reality experiences.

The Research Scientist role at Meta offers a unique opportunity to innovate in computer vision, machine learning, and AI. As a Research Scientist, you will collaborate with world-class teams to solve complex problems, develop cutting-edge algorithms, and transform Meta’s products and services to serve billions of users better worldwide.

This guide will walk you through the interview process for the position, including what to expect, common Facebook (Meta) research scientist interview questions, and valuable preparation tips. Let’s get started on your journey to joining one of the top tech companies in the world!

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Meta 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.

The whole recruiter call usually spans about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Meta’s technical screenings are typically conducted virtually, involving video conference and screen sharing. Questions in this interview stage might revolve around machine learning, statistics, programming, and Meta’s specific systems.

Depending on the role, you might encounter coding exercises, algorithmic problem-solving, and data structure questions. Reviewing data structures, algorithms, and key concepts in your area of expertise is highly recommended.

Presentation Round

Upon passing the technical screening, you may be asked to deliver a presentation. This presentation aims to assess your ability to communicate complex ideas effectively and demonstrate your expertise. Typical topics for the presentation might include past projects, a specific problem area, or hypothetical scenarios related to Meta’s domain.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop, which might now be virtual depending on Covid-19 restrictions. Multiple interview rounds, varying by role, will be conducted during your day at the Meta office. These interviews will evaluate your technical prowess, including programming, machine learning capabilities, and problem-solving skills.

If you were assigned take-home exercises, a presentation round may also be included during the onsite interview.

Typically, interviews at Facebook vary by role and team, but commonly research scientist interviews follow a fairly standardized process across these question topics.

1. Would you think there was anything fishy about the results of an A/B test with 20 variants?

Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?

2. What would you do if friend requests on Facebook are down 10%?

A product manager at Facebook reports a 10% decrease in friend requests. How would you address this issue?

3. What metrics would you use to determine the value of each marketing channel?

Given all the different marketing channels and their respective costs at a company selling B2B analytics dashboards, what metrics would you use to evaluate each channel’s value?

4. How would you test if changing Facebook’s composer feature to a “+” button is a good idea?

Facebook wants to change the user interface of the composer feature to a “+” button at the bottom of the page. How would you test if this change is beneficial?

5. What are the Z and t-tests, and when should you use each?

Explain Z and t-tests, their uses, their differences, and when to use one over the other.

6. Write a function find_bigrams to return a list of all bigrams in a sentence.

Write a function called find_bigrams that takes a sentence or paragraph of strings and returns a list of all its bigrams in order. A bigram is a pair of consecutive words.

7. Write a query to find out how many users have opened an email.

Given a table called events that keeps track of every user’s actions, write a query to find out how many users have opened an email.

8. Write a query to select the top five most expensive projects by budget to employee count ratio.

Given two tables, projects and employee_projects, write a query to select the five most expensive projects by budget to employee count ratio, accounting for duplicate rows in the employee_projects table.

9. Write a query to get the last transaction for each day from a table of bank transactions.

Given a table of bank transactions with columns id, transaction_value, and created_at, write a query to get the last transaction for each day. The output should include the id, datetime, and transaction amount, ordered by datetime.

10. Write a query to get the average order value by gender.

Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender. Round the answer to two decimal places.

11. What is a confidence interval for a statistic and why is it useful?

A confidence interval provides a range of values within which a population parameter is expected to lie with a certain level of confidence. Explain its usefulness and how to calculate it.

12. What are Z and t-tests, and when should you use each?

Describe the Z and t-tests, their purposes, differences, and scenarios for appropriate use.

13. Is it worth playing a game where you win $21 if the sum of two dice equals seven, but pay $10 per roll?

Analyze the expected value of the game to determine if it is worth playing.

14. How would you explain a p-value to a non-technical person?

Provide a simple and clear explanation of a p-value for someone without a technical background.

15. What is the expected number of good ads rated by different types of raters?

• Calculate the expected number of good ads if 100 raters each rate one ad independently.
• Calculate the expected number of good ads if one rater rates 100 ads.
• Determine the probability that a rater was lazy if an ad is rated as bad.

16. What metrics would you use to track the accuracy and validity of a spam classifier model?

Assume you have built a V1 of a spam classifier for emails. What metrics would you use to evaluate the model’s accuracy and validity?

17. How would you evaluate the success of advertising for an event with a 10% weekly increase in search clicks?

You are tracking the success of advertising for an event, and there has been a 10% weekly increase in search clicks. Is this good or bad? How would you determine if the advertising needs improvement?

18. How does random forest generate the forest and why use it over logistic regression?

Explain how a random forest algorithm generates its forest. Additionally, discuss why you might choose random forest over other algorithms like logistic regression.

19. How would you build a restaurant recommender on Facebook, and what are potential concerns?

Describe how you would gather data and build a restaurant recommender system on Facebook. What are some potential downfalls or concerns with adding this feature?

20. How would you test if having more friends increases the probability of being an active Facebook user after 6 months?

Design a test to determine whether having more friends now increases the likelihood that a Facebook member remains active after 6 months.

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 Meta interview include:

• Be Prepared for a Technical Deep Dive: Meta interviews often involve a deep dive into your technical skillset. Brush up on algorithms, data structures, and system design, and consider trying our AI interviewer to help you with the technical interview.
• Demonstrate Problem-Solving Skills: Meta values your problem-solving abilities. Be ready to tackle complex problems and explain your thought process clearly. Highlight how you approach problem-solving in your past experiences.
• Communicate Effectively: Your ability to communicate complex ideas succinctly is crucial. Practice delivering concise and impactful presentations, and be ready to discuss your projects and ideas thoroughly. Try our mock interview to help you improve your communication skills.

By following these tips, we are sure you’ll be more confident and thoroughly prepared for your interview at Meta!

What’s the average salary of a Meta Research Scientist?

How is the company culture at Meta?

Meta champions a culture of innovation, diversity, and learning. You will be encouraged to take risks, think creatively, and collaborate with a global team. It’s a fast-paced environment where your contributions can significantly impact the future of technology.

Are there any job openings at Meta?

As of writing (Sep 2024), there are openings for the Meta research scientist position! Check out our job board to see more details.

The path to joining Meta is methodical yet thrilling. It involves stages like initial screenings, technical interviews covering machine learning and statistics, and comprehensive presentations.

By showcasing your proficiency, you’ll stand out in this fulfilling field. Embrace the journey, tap into Meta’s extensive interview preparation resources, and transform your aspirations into reality.

Good luck with your interview! Explore further by visiting our main Meta interview prep guide for more insights and tips.