Facebook Data Scientist Position Guide

Find out what it means to be a data scientist at Facebook!

Introduction
Facebook, Inc. is a social media conglomerate that “gives people the power to build community and bring the world closer together.” It includes the social media platforms Facebook, Facebook Messenger, Instagram, and WhatsApp, as well as other products such as Giphy, Mapillary, and Oculus VR. Founded in 2004, the company now has over forty thousand employees across the United States, with a user base of over 3 billion people worldwide.

As of 2021, Facebook has over 1 billion stories and 100 billion messages shared among its users every day, not to mention the over 200 million businesses on their platform. This means Facebook has one of the richest data sets in the world, with a massive volume of information on user activity and interactions built on top of a robust global infrastructure. Data roles at Facebook create actionable insights for business, marketing, and engineering products.

Find more information about working at Facebook on their Careers page. Learn more about Facebook’s Data & Analytics teams here. Be sure to also check out Facebook’s Career FAQs.

Salaries of Facebook Data Positions

Here's a quick overview of the types of data positions at Facebook and their respective salaries, with a comparison to the national average.

Total compensation at Facebook also includes health & dental insurance, life insurance, 401k with company match, stock RSUs, and bonuses.

Let's take a look at additional qualifications for these roles.

Roles and Required Experience for Data Positions at Facebook

	Data Analyst	Data Scientist	Data Engineer
Minimum Qualifications	3+ years of experience designing, running, and presenting data analysis	Bachelors/Masters Degree with 4+ years (or PhD with 2+ years) of experience working within an analytical role	5+ years experience in the data warehouse space
	2+ years of experience querying data (SQL or similar) or performing statistical analysis (R, Python, or similar)	2+ years of experience communicating the results of analyses to leadership teams to influence the strategy	5+ years experience in custom ETL design, implementation and maintenance.
			7+ years experience with schema design and dimensional data modeling.
Collaborative Experience	Experience working autonomously and collaboratively	Experience working independently and as a member of a cross-functional team	Experience managing and communicating data warehouse plans to internal clients
	Experience explaining data analyses to cross-functional teams who are not focused on analytical work	Experience in Tech industry leading large projects	Experience analyzing data to identify deliverables, gaps, and inconsistencies
Analytical Experience	Analytically driven with experience manipulating large data sets in SQL or equivalent, and drawing actionable insights from data	Experience in using SQL to query and manipulate large data sets for analysis	Experience with large data sets, Hadoop, and data visualization tools
		Experience with ML and statistical knowledge	Experience with data architecture, data modeling, schema design, and software development
Preferred Qualifications	Advanced degree	6+ years of experience in all the above minimums	Bachelor's degree in Technical Field, Computer Science, or Mathematics

Types of Data Positions at Facebook

Data Scientist teams perform a vital function to every team at Facebook, and there are many teams throughout the company at varying levels of the organization. This goes from the broader financial and operation analysts to a wide range of product-specific roles across Facebook's multitude of platforms. The responsibility and focus of a data role will vary depending on the department you are hired for.

These departments include:

Product Analytics

With Facebook’s reach across so many platforms, it’s only natural they have Data Science teams dedicated to each and every one. There are the most open data roles in this area, especially given all the different products that Facebook provides. For perspective, there are teams dedicated to Instagram stories, Instagram product performance, the Facebook app, Facebook Ecosystems, the Messenger platform, payment analytics, and more.

A data role in Product Analytics will:

• Apply expertise in quantitative analysis, data mining, and the presentation of data, seeing beyond the numbers to understand how users interact with consumer and business products
• Solve problems and identify trends and opportunities
• Inform, influence, support, and execute product decisions and launches

Data Engineers primarily fall into this category, working cross-functionally to:

• Architect build and launch new data models that provide intuitive analytics
• Design and develop new systems and tools to enable folks to consume and understand data faster
• Define problem statements, collect data, and make recommendations

Advertising

Driving Facebook's largest source of revenue, advertising teams work to create meaningful impressions for over 1.5 billion people on Facebook products every day. Using cutting-edge Machine Learning algorithms, these teams create an impact at a global scale to improve the relevance and quality for both users and advertisers.

A data role in Advertising will:

• Do market research and convert the research insights into building product strategy
• Leverage data to inform the right business decision, such as designing how to evaluate the product performance and whether they should be launched
• Influence product teams through presentation of data-based recommendations, communicating state of business and experiment results

Business & Finance

Business and finance teams play a unique role in Facebook, coordinating across a number of groups in the company in a highly cross-functional and partner-facing role. These teams deliver key financial insights and business trends to management and other teams.

• Analyze and model the financial ecosystem, developing actionable insights to enable strong financial decision making
• Influence the direction of the business by effectively communicating results to the rest of the team and company leaders
• Assess market opportunities and analyze current business performance to extrapolate current and historical trends into forward-looking forecasts

Now that you know more about the roles and responsibilities of data teams at Facebook, here's how the interview process works.

Outlining the Data Scientist Interview Process at Facebook

Facebook has a fairly standard and extensive interview process, from the initial phone call screening through the hiring manager interview, and finally the on-site interview.

Application & Initial Screen

After the (obvious) first step of submitting your resume, there is an initial screening phone call with a recruiter. This is a short half-hour conversation where the recruiter explains the role and the upcoming interview process, with behavioral and product sense questions to briefly discuss your background and understanding of Facebook.

Hiring Manager/Team Member Call

Next up is an hour-long call with a hiring manager or team member, which will go more in-depth about your experiences and technical expertise. This will include scenario-based questions related to the role and a coding segment.

Full Day On-site Interview

Unlike some companies, Facebook does not do a take-home data challenge. Instead, there typically is a full day on-site interview. This includes meetings with a variety of team members you will (ideally!) soon be working with, including three rounds of technical interviews and a behavioral interview, with a lunch break in between.

Note: the interviews will be virtual and the interview format may vary for the duration of the pandemic.

Types of Data Scientist Interview Questions at Facebook

The interview questions at Facebook generally fall into the following categories. We’ve included some real examples of each, and have discussion pages and walkthroughs linked for some of the questions as well.

Behavioral Questions

Interviews always include the typical questions about your background and experiences, with many variations of "Tell me about a time where…"

• What were you doing on your very best day at work?
• What's your plan for the first sixth months?
• What was the most difficult thing you experienced in a project?

We discuss how to approach behavioral questions in an interview here.

Product Sense & Business Cases

These questions help gauge your interest in Facebook as a company as well as your knowledge of Facebook products.

• Creation of Facebook user groups has gone down by 20%, what will you do?
• What do we recommend to users through the hashtag?
• If 70% of Facebook users on iOS use Instagram, but only 35% of Facebook users on Android use Instagram, how would you investigate the discrepancy?

Data Analysis & Coding

This portion of the interview tests your coding ability, covering technical details of the code with specific examples, often sequential join questions that start off at a basic level and become more and more complicated.

• What is the difference between a left join vs. a union vs. a right join?
• What is the overall friend acceptance rate by date?
• Write a query to calculate the distribution of comments by the count of users that joined Facebook between 2018 and 2020, for the month of January 2020.

Check out our post on the Most Common SQL Data Analyst Interview Questions by Facebook

Modeling Techniques

These questions cover practical applications of your coding ability and how you approach data problems. Don't forget the natural followup to any modeling question: "How can you tell that your model is working?"

• How would you create a model to find bad sellers on Marketplace?
• How would you confirm that users’ high school data is real?
• How would you test whether having more friends now increases the probability that a Facebook member is still an active user after 6 months?

Quick Tips

• Do your research about the role and interview process. (You're here already so that's a good start!)
• Explain your thought process when doing coding questions. It’s important that your interviewer knows how you approach solving problems.
• Spend some time to take stock of your skillset and assess what you need to work on, whether it be an area of SQL syntax or your interview skills.

Additional Resources

Remember to read up on Facebook’s Data & Analytics team and to explore the Facebook Careers FAQ. Check out our forum of Facebook’s Data Science interview questions here. We also write blog posts that walk you through how to solve specific interview questions in our Data Science Interview Questions series. Be sure to research the most recent interviews and salary information for the role on Glassdoor. Levels.fyi also has up-to-date information on salaries and benefits.