Meta (Facebook) Data Science Internships: What to Expect & How to Land the Job (Updated in 2024)

Meta (Facebook) data science internships are some of the most coveted intern positions in data science.

That’s due in part to the incredible work experience Meta interns receive. Meta data science interns gain hands-on training and work on actual data science problems. As a result, a Meta internship instantly makes your resume more attractive and can help to launch your data science career.

Yet, Meta’s data science intern program is one of the most competitive. Just 200 to 300 interns are accepted for summer programs and even fewer in the fall. Therefore, to land the job, you have to nail the interview and have the right skills.

We wanted to outline what you can expect as a data science intern at Meta. This article will answer your most basic questions like:

• What do Meta data science interns do?
• How much do data science internships pay?
• And how do you land a data science internship at Meta?

At Meta, the internships vary from year to year, so it is better to look at the Meta Career Page for the latest open opportunities. Some of Meta’s internship programs we’ve seen in the past include:

1. Enterprise Engineering Internship
2. Software Engineering Internship
3. Data Science Internship
4. UX Researcher Internship
5. Content Design Internship

You may also check Interview Query’s Job Board for relevant job postings.

It’s no secret that a conglomerate as big as Meta is going to give out big paychecks, even for interns. Some data science positions at Meta pay up to $171,000 a year, and that’s before adding in any of the bonuses, benefits, or equity. So, most likely, interns can enjoy a salary of at least half of the full-time paycheck.

However, money is not the only reason so many young data scientists are chasing a Meta job. There are so many other benefits employees can get at Meta. Let’s have a look at some of them:

• Remote/Hybrid Work - While this is a common benefit in the tech industry, especially for data scientists, it’s still worth mentioning that Meta does provide a remote work option for employees.
• Office amenities - Based on experience from ex-Meta employees, the offices offer a lot of amenities to make employees feel as comfortable as possible. For example, Meta’s headquarters in California offer perks such as laundry service, a barbershop, an arcade room, free valet parking, free meals, and more.
• Health and wellness program - Another huge benefit for Meta employees is the health coverage program. It covers everything from mental health resources to medical, dental, vision, and more. Furthermore, these benefits extend to other family members, like spouses, partners, and children.
• Paternal and maternal leave - Employees get four months of paid parental leave with full-time (base) pay.
• Life insurance and retirement plan - Employees also get a retirement plan and life insurance.
• Vacation (US-only) - US-based employees get 21 days of paid time off, 12 paid holidays, 2 additional days of paid time off, unlimited paid sick leave, 20 days of emergency paid time off, and a few more time-off benefits that accumulate over the years.

So, we covered what you can anticipate from Meta and its internship programs, but now, let’s look at Meta’s expectations and your responsibilities as an intern.

As a Meta data science intern, you will be assigned a mentor, who will guide you on many tasks ranging from data extraction to data analysis to visualization. Ultimately, the work that you do is determined by your experience.

Junior-level internship programs focus on tasks like data analytics, A/B testing, UX testing and more. For example, LinkBench, Meta’s database benchmark, was developed by a data engineering intern.

Although Meta’s data science programs will provide ample learning time, they’re also tailored to aspiring data scientists who can develop solutions and contribute. As an intern, you won’t be a coffee-getter. Instead, you’ll develop real-world solutions and work on 1-2 data science projects during your internship.

As a Junior data science intern at Meta you will be expected to:

• Work closely with other teams to propose logical strategies to facilitate the decision making process in the company.
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organization.
• Use machine learning tools and statistical techniques to provide solutions to problems.
• Test data mining models to select the most appropriate model for use on a project.
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.
• Create clear reports that tell compelling stories about how customers or clients work with the business.
• Assess the effectiveness of data sources and data-gathering techniques, while offering improvements to their data collection methods.

Experienced interns, who are usually PhD candidates, work on complex data science projects and research, developing and testing new machine learning approaches, advanced analysis and attribution modeling, and more.

At the time of writing, there are more than 30 data science-related internships, so naturally, every position will have different requirements regarding technical knowledge, social skills, and qualifications.

But here are the typical requirements for Meta internships:

Technical Skills

When starting as a data scientist intern at Meta or any other tech company, your most vital points will be your technical skills, specifically in:

Programming and Software Applications

Data science is all about turning that raw data into easily processed information, and the only way to churn out actionable insights is through programming. So, mastery in Python or R programming is essential for a data scientist intern.

Being tech-savvy with software applications can also be a huge benefit.

Statistics and Probability

As a data scientist for a tech company, you need to have a deep understanding of statistical concepts and know how to utilize algorithms, make decisions, and follow best practices to create insights.

Artificial Intelligence and Machine Learning

With the AI boom in the past couple of years, the global machine-learning market grew 120% in 2023. So, naturally, Meta greatly appreciates students who understand machine learning algorithms and frameworks like TensorFlow or PyTorch.

Data Manipulation and Data Visualization

Advanced understanding of tools like NumPy and SQL for data manipulation and wrangling is another technical must-have skill for these data science internship programs. But knowing how to visualize this data is just as important as well, so make sure you have a decent grasp of tools like Seaborn or its alternatives.

Minimum Education and Experience Qualifications

Anyone looking to enter a Meta data science internship program needs to have a bachelor’s degree. However, depending on the position, Meta might also require a master’s or a PhD, either already obtained or in process.

The degrees required generally are in the following fields: computer science, computer engineering, statistics, and operations research, or other degrees in quantitative fields.

Working Experience

In terms of experience, Meta usually doesn’t require any job-related experience with data science, as these internships are primarily for fresh graduates.

However, Meta will find it valuable if someone has worked with a team and developed cooperative and communicative skills. The ability to solve complex problems and find alternative solutions to data-related problems can also be a huge plus.

Data science or research-related solutions for projects on repositories like GitHub can also earn you some extra points, especially if these solutions are widely used in the data science community.

While an internship at Meta is a very rewarding experience for any intern, a paycheck is required. Fortunately, Meta understands the importance of supporting its interns with reasonable pay.

Based on information from GlassDoor, Meta intern salaries range from $83,000 to $149,000. Keep in mind, that this information is based on interns in multiple fields, not just those in the data science field. However, a salary around the $100,000 mark makes sense for interns, as the starting salary for many data science-related jobs at Meta is around $208,000 to $299,000.

You can apply for a position at Meta online through their career page. Some universities are also lucky enough to bring representatives on campus, where recruiters can conduct face-to-face interviews. The Meta interview consists of two rounds:

Technical interview: This takes place online and is about 60-75 minutes long. You are given a link to an online collaborative editor, where you code while talking to your interviewer. During the first 15 minutes, your interviewer goes through your resume and asks you about your projects and career. The next 60 minutes are spent solving 2 coding questions. The first question is generally easier. The last 5 minutes are for you to ask the interviewer any questions you may have about life at Meta.

Onsite interview: This can also happen online instead of onsite depending on your location and the circumstances, especially in the post-COVID environment. If your interview is onsite, have fun! You’ll get a tour of Meta’s headquarters and have the chance to talk and network with a host of current employees. The coding part has the same structure as interview one, but it is longer with harder questions. There will be design and behavioral questions also asked in the second round.

Data science interview questions tend to fall into four main categories, including data analysis, product sense, statistics and data modeling, and your interviewer can pick any question at random for you to answer.

The key is to prepare for a variety of different questions, with a main focus in preparation on the skills you’re weakest in. Some example Meta data science internship interview questions include:

1. Given an integer array, move all elements that are equal to 0 to the left while maintaining the order of other elements in the array.

2. Given a list of intervals, merge all the overlapping intervals to produce a list that has only mutually exclusive intervals.

3. Given the head pointers of two linked lists where each linked list represents an integer number (each node is a digit), add them and return the resulting linked list.

4. Given two sorted linked lists, merge them so that the resulting linked list is also sorted.

5. Convert a binary tree to a doubly linked list so that the order of the doubly linked list is the same as an in-order traversal of the binary tree. After conversion, the left pointer of the node should be pointing to the previous node in the doubly linked list, and the right pointer should be pointing to the next node in the doubly linked list.

6. Given a binary tree and a number ‘S’, find all paths from root-to-leaf such that the sum of all the node values of each path equals ‘S’.

7. Given a dictionary of words and an input string tell whether the input string can be completely segmented into dictionary words.

8. Given a list of daily stock prices (integers for simplicity), return the buy and sell prices for making the maximum profit. We need to maximize the single buy/sell profit. If we can’t make any profit, we’ll try to minimize the loss.

9. Given a double, ‘x’, and an integer, ‘n’, write a function to calculate ‘x’ raised to the power ‘n’.

10. Serialize a binary tree to a file and then deserialize it back to a tree so that the original and the deserialized trees are identical.

11. How would you analyze user behavior and track metrics like click-through rates, engagement, and satisfaction to improve Facebook’s search for activities in San Francisco?

12. Suppose you have an events table that tracks user activities on a website. Write a query to identify and label each event with a session number.

Every internship for different job positions will have varying interview requirements, but there are still many similarities when it comes to evaluating technical skills.

Here are some tips for interviewing:

• Don’t worry about dressing up for the interview. Meta doesn’t stress about dress code and even promotes more casual wear, so don’t stress too much about it.
• The interview will last around 60 minutes. Expect a few minutes at the beginning to introduce yourself, 40–50 minutes for the technical screening process, and 5–10 minutes for any questions they or you might have.
• Prepare for a coding test. The interview will most likely have a coding screen, so prepare well beforehand. Usually, the screening is for Python.
• Get ready for an SQL test. The interview testing will be split into coding and (most commonly) SQL. There are exercises on Meta’s website to get you up to date. Generally, you should know SQL concepts like Joins, UNION vs UNION ALL, aggregations, case statements, filters, etc.
• Become familiar with the role you’re after. Expect a lot of questions on why you want that position, how you will fit in, and your career plans.
• Come up with unique questions related to the role and the work environment. Most interviews end with: “Do you have any questions?” And, even though it’s a yes or no question, you should always answer yes. At Meta, they’ll expect you to ask some thoughtful questions to showcase your interest.
• Use Meta’s interview prep guide.
• You can also try mock interviews that simulate real-world interviews and give you that boost of confidence you need before the real thing.

Meta has high standards for choosing its data scientists because data is probably their most valuable asset. Combined with the highly competitive environment, i.e., hundreds, or even thousands, of other data scientists chasing those internships, a lot of preparation is needed.

However, with our Facebook (Meta) interview guide, you should be able to end up on top! You can also check out data science courses at Interview Query to ensure your technical skills are on par with Meta’s expectations.