Facebook Data Scientist Interview: The Ultimate Insider Guide

Are you dreaming of becoming a data scientist at Facebook (Meta)? Brace yourself, because the interview process is as challenging as it is rewarding. In this comprehensive guide, we’ll equip you with an insider’s perspective on acing the Facebook data scientist interview, from mastering the questions to nailing the preparation. Let’s dive in!

The Interview Gauntlet: A Four-Stage Process

Before you can join the ranks of Facebook’s data science elite, you’ll need to navigate a multi-stage interview process that typically spans four to eight weeks. Here’s what you can expect:

1. Resume Screen: Your journey begins with a recruiter evaluating your resume to ensure you meet the position’s requirements. Competition is fierce at this stage, so make sure your resume is tailored to showcase your relevant experience and achievements.

2. Recruiter Phone Screen (15 minutes): If your resume passes muster, you’ll have a brief call with a recruiter to discuss your background and potentially tackle some SQL and product analysis questions. Don’t underestimate this initial screening – it’s your first opportunity to impress.

3. Technical Screen (1-2 interviews, 45 minutes each): Prepare to showcase your technical prowess in one or two interviews covering SQL, analysis cases, and other data science concepts. Think of these as a warm-up for the main event.

4. Onsite Interviews (4 interviews, 30 minutes each): The final hurdle is a series of four interviews, each focusing on a different aspect of the data scientist role. You’ll tackle product interpretation, applied data analysis, quantitative reasoning, and technical coding challenges.

Throughout the process, your recruiter will be your guide, facilitating the transitions between stages and providing valuable insights into what to expect.

The Question Onslaught: Mastering the Interviews

Now that you know the process, let’s dive into the types of questions you’ll encounter at each stage. Brace yourself, because Facebook’s data scientist interviews are known for their depth and complexity.

Analysis Case: Product Interpretation

In this product case study, you’ll need to demonstrate your ability to interpret user behavior using data and metrics. Expect questions that challenge you to analyze Facebook’s products, suggest improvements, and explain how you would measure the success of those changes.

• “What’s your favorite Facebook product, and how would you improve it?”
• “How would you measure the success of the News Feed?”
• “Activity in Facebook user groups is down by 20%. What would you do?”

Analysis Case: Applied Data

Building on the product interpretation case, this interview will task you with solving a specific product-related problem using a provided dataset. You’ll need to frame the problem, propose metrics, consider A/B testing, and weigh technical trade-offs.

• “How would you use data to confirm that users’ high school data is real?”
• “How would you evaluate the impact of parents joining Facebook on teenage users?”
• “Given a data table, how would you create a model to detect spam?”

Quantitative Analysis

Get ready to flex your statistical muscles! In this portion, you’ll face questions that test your understanding of mathematical, statistical, and probabilistic concepts, as well as your ability to apply them to real-world business problems.

• “How do you explain p-value to non-technicians?”
• “What is Recall metric? Can you explain it from scratch?”
• “Explain your process for conducting A/B testing.”

Technical Analysis

As a Facebook data scientist, you’ll be working with one of the most extensive data sets in the world. In this coding interview, you’ll primarily face SQL-related problems, requiring you to write queries with proper syntax and demonstrate your proficiency in data manipulation.

• “Given a table with user IDs and visit dates, find the top 100 users with the longest continuous visit streak as of yesterday.”
• “Given a database of posts and comments, determine the average number of conversations happening in the comments per post.”
• “What’s the difference between a left join, a union, and a right join?”

Behavioral Questions

In addition to the technical challenges, you’ll also face behavioral or “resume” questions that assess your communication skills, motivations, and cultural fit for Facebook. Use these opportunities to tell your story, highlight your passion for data science, and demonstrate alignment with Facebook’s values.

• “Why Facebook?”
• “Describe a data and analytics project you’ve worked on.”
• “What has been the biggest challenge you’ve taken on?”

Preparation Strategies: Your Path to Success

Preparing for the Facebook data scientist interview is no small feat, but with the right strategies, you can maximize your chances of success.

1. Learn About Facebook’s Culture: Before investing significant time in preparation, ensure that Facebook’s culture and values resonate with you. Talk to current or former employees, read about Facebook’s core values, and immerse yourself in the company’s ethos.

2. Practice by Yourself: Utilize resources like Facebook’s mock interview video, case study guides, and practice questions to hone your skills. Study statistics fundamentals, practice SQL queries, and conduct mock interviews with yourself to refine your communication abilities.

3. Practice with Peers: While solo practice is valuable, it’s also crucial to simulate the interview experience with peers. Seek out friends or colleagues familiar with data science interviews to provide feedback and help you improve your delivery.

4. Practice with Ex-Interviewers: For the most accurate and valuable feedback, consider practicing with experienced ex-interviewers from Facebook or other leading tech companies. Services like IGotAnOffer offer 1-on-1 coaching sessions with former interviewers, providing you with invaluable insights and personalized guidance.

Remember, preparation is key, but it’s also essential to maintain a positive mindset and enthusiasm throughout the process. Facebook is seeking not only technical expertise but also individuals who embody the company’s values and can contribute to its dynamic culture.

By combining dedicated preparation, a deep understanding of Facebook’s expectations, and a passion for data science, you’ll be well-equipped to tackle the Facebook data scientist interview and potentially secure your dream job.