IN THIS ARTICLE
- What does an intern at Facebook do?
- What is the process to get a data science internship at Facebook?
- Are interns working in data science at Facebook paid?
- What’s it like to be an intern in data science at Facebook?
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As one of the most influential technology companies in the world, with tens of thousands of employees spread across dozens of global teams and a family of apps that defines social media, Facebook’s internship programs are designed to attract the best and brightest.
Instead of having a blanket internship program, though, Facebook offers demographic-specific tracks, such as Facebook University—an eight-week paid summer internship for qualified individuals from underrepresented backgrounds; a University Grad track for recent college graduates; and a traditional twelve-week summer internship.
True to its reputation as a fast-moving company, it expects its interns to be quick-thinking and adaptable—Facebook prides itself on having interns directly work on new products, solve analytical problems, and ship code that affects the experiences of more than a billion global users.
Facebook offers some of the technology industry’s most coveted and highly paid internships, many of which lead to permanent, full-time positions. Read on to learn more about Facebook’s data science internships and how to get a foot in the door.
What does an intern at Facebook do?
The skills and experience levels of data science interns vary depending on the kind of internship undertaken. As far as minimum qualifications go, though, data science interns—whether Facebook University analytics candidates or seasoned PhD-holding data junkies—are expected to be familiar with programming languages such as SQL, Python, and Java, and scripting languages such as PHP or Perl. A background or ongoing studies in Statistics, Applied Mathematics, Computer Science, or a related technical field is also preferred.
With a sufficient technical foundation, Facebook’s data science interns are thrust into the deep end and work on real-world projects such as building reporting dashboards that track key business metrics and performing large-scale data analysis to identify actionable insights. Former interns have also worked on projects affecting application speed, device capabilities, and navigational patterns. Facebook’s rainbow pride filter—launched after the U.S. Supreme Court legalized gay marriage in 2015 and used by millions of people—was built by two interns. The database benchmark LinkBench was also co-developed by an intern.
As part of the data analytics team, data science interns use different quantitative approaches to help Facebook make sense of its troves of collected data, make recommendations for improvements to a particular product, and ultimately have an impact on the business. Data science interns also collaborate with a product manager and an engineering team to manage decisions, classify leads so that teams work on the most valuable cases, and suggest improvements in tools and techniques to help both scale the team and improve Facebook’s product.
“Almost immediately I felt like the work I was doing was important,” said JJ Maxwell, a former data science intern at Facebook. “From being featured in VP emails, to discussions about a Zuck review of my work (twice), I quickly realized this internship was much different [from] the previous five I had done.”
What is the process to get a data science internship at Facebook?
Landing an internship at Facebook requires showing the application reviewers that you have both the technical chops to handle database querying challenges and the right attitude to thrive in a competitive, fast-paced environment.
“Being persistent around craving knowledge” is one trait that Facebook looks for in its interns, according to Hyla Wallis, Facebook’s former university programs and operations manager. “We talk about ‘lean-in’ circles, surrounding yourself with people who are looking to achieve similar goals as you…[and] people who are working in a way to help others grow.”
Below are steps to follow that can bring you closer to a Facebook internship.
- Step 1: Build on your skills.
A baseline requirement for qualified applicants is knowledge of programming languages such as SQL or Python, and some experience in solving analytical problems using quantitative approaches (or equivalent). If your prior degree-program didn’t help you develop these skills, or if you’re rusty, consider doing a refresher through independent study or a mentor-supported bootcamp.
- Step 2: Build that CV and portfolio
While Facebook’s internship programs list many preferred qualifications, a strong CV and accompanying portfolio will help hiring managers see who has the drive and initiative to solve problems and complete projects. If you’ve contributed to research or worked with professors or graduate students on projects, share it. If you’ve worked on your own projects by wrangling publicly available data sets, document it.
“Companies want people who have the potential to come in and make an impact,” said Chester Leung, a software engineer who landed an internship at Facebook after including his research and open source work on his résumé. “Showing that you have the proper mindset and relevant experience is one step in the right direction.”
The same is true for data scientists looking to get a foot in the door.
- Step 3: Prep your application
Some internships, such as Facebook University’s eight-week program, require additional job application procedures such as essay writing. In a recent application cycle, candidates were asked to answer the following questions:
“From the role descriptions provided for Data Engineering and Data Science, please rank your choice in order of preference. In two paragraphs, please explain why you’re passionate about your top choice.”
“We want to better understand your experiences and interests relevant to data and analytics. Describe a previous project you’ve worked on that involved data.”
“Over the last decade, data has transformed the way the world works. Describe an area where you think data will change the world in the next five years. Which lesson(s) from the evolution of data in recent years would you draw on to help make sure data changes the world in positive ways going forward?”
- Step 4: Shine in the interview
If you make it to the first general interview, which is typically conducted over the phone, then you want to be prepared on multiple fronts: showing that you are deeply familiar with and understand Facebook’s mission and suite of products, and being able to discuss your background and previous work.
If you make it to subsequent rounds, expect to be tested on your technical chops—former interns have had to use SQL and Python to provide solutions to product analytics questions and perform basic statistical functions.
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Are interns working in data science at Facebook paid?
In addition to one of the most competitive salaries for interns in the U.S., the position also comes with a slew of perks: round-trip airfare to their work location (Facebook has major hubs in Menlo Park, Seattle, Austin, and New York City), intern housing or a monthly housing stipend, complimentary meals, bike rental, and access to employee shuttles. During the Covid-19 pandemic, Facebook has created remote work opportunities for its employees.
At the completion of the internship, many interns are considered for full-time roles or returning opportunities.
What’s it like to be an intern in data science at Facebook?
The experience of being a data science intern varies depending on the team with which an intern works. That said, data science interns at Facebook commonly report being assigned a long-term project with milestones and oversight from a mentor, while also collaborating with teams of researchers, analysts, designers, and code builders on projects with a quicker turnaround—all of which relate to problems the company is trying to solve.
Many interns are given the trust and flexibility to decide how they want to approach their projects, are able to contribute to real-world projects in meaningful ways within their first week, and can see the effects of their work out in the wild.
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