Meta Research Scientist Interview Guide

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., 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 be at the forefront of innovation in fields like 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 better serve billions of users worldwide.

This guide will walk you through the interview process for the Research Scientist position at Meta, including what to expect, common questions, and valuable preparation tips. Let’s get started on your journey to joining one of the most dynamic and impactful tech companies in the world!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Meta. Whether you were contacted by a Meta 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 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.

In some cases, the Meta 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 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.

Quick Tips For Meta Interview Success

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 are often deep dives into your technical skillset. Brush up on algorithms, data structures, and system design. Use platforms like LeetCode to practice coding challenges.
• 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 and clearly is crucial. Practice delivering concise and impactful presentations, and be ready to discuss your projects and ideas thoroughly.

Start preparing and learn about how to prepare for your interview with Meta’s interview guide, tips, and interactive experiences available on their website. Visit Meta interview prep for more details.

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 what Z and t-tests are, their uses, the differences between them, and when to use one over the other.

1 - 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.

2 - 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.

3 - 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.

4 - 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.

5 - 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.

1 - 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.

2 - 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.

3 - 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.

4 - 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.

5 - What is the expected number of good ads rated by different types of raters? 1. Calculate the expected number of good ads if 100 raters each rate one ad independently. 2. Calculate the expected number of good ads if one rater rates 100 ads. 3. Determine the probability that a rater was lazy if an ad is rated as bad.

1 - What metrics would you use to track 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?

2 - 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?

3 - 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.

4 - 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?

5 - 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.

FAQ for Meta’s Research Scientist Position

Q: What is the interview process like at Meta for a Research Scientist position?

A: The interview process at Meta involves an initial HR phone screening, followed by technical interviews comprising machine learning, statistics, and behavioral questions. A presentation may also be required, and the process typically includes multiple rounds—all designed to evaluate your skills and cultural fit.

Q: What types of questions should I expect during the technical interview?

A: Be prepared for a mix of machine learning, statistics, and behavioral questions. Your problem-solving abilities will be tested with coding challenges, often sourced from platforms like LeetCode. Dive deep into your past projects and experiences—this is your time to shine!

Q: What qualifications are Meta looking for in a Research Scientist?

A: Meta values strong academic backgrounds in Computer Science, Computer Vision, or related fields, often requiring a Ph.D. Additionally, your experience with machine learning frameworks like TensorFlow or PyTorch, and a proven track record of research via publications or patents, are essential.

Q: How is the company culture at Meta?

A: 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 have a significant impact on the future of technology.

Q: How should I prepare for my interview at Meta?

A: Preparation is key! Focus on mastering your technical skills and practicing coding problems. Familiarize yourself with Meta’s products and services. Brush up on your knowledge of machine learning and statistics, and be ready to articulate your experiences and research effectively. Confidence is crucial, so practice thoroughly and stay positive!

As the landscape of social technology continues to evolve, Meta remains at the forefront, seeking innovative and visionary research scientists to propel the next generation of immersive experiences. The path to joining Meta is methodical yet thrilling, involving stages like initial screenings, technical interviews covering machine learning and statistics, and comprehensive presentations.

Meta’s interviewers are notable for their professionalism and friendly demeanor, making a potentially stressful process more approachable. Despite occasional setbacks due to external factors like hiring freezes, candidates are encouraged to persist and prepare rigorously using resources like LeetCode.

By showcasing your proficiency in computer vision, machine learning, and data science, and honing your problem-solving skills, you’ll stand out in this exciting 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 Meta’s interview prep guides for more insights and tips. Dive into the world of Meta, where your research could define the future of communication and connectivity. ????