Google offers some of the most competitive and highly paid internships in the world. Read on to learn about how to land a data science internship at Google.
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Google is one of the most dominant players in the technology industry. From its search engine used by billions of people worldwide; to its slew of software and platforms, which includes YouTube, Gmail, Hangouts, Google Maps, and Google Drive; to its advertising and retail tools, few companies are as influential or have as great an impact on the world as Google. It’s no surprise then that the company’s internships are highly coveted and designed to attract the best and brightest.
Google offers internships across three categories: engineering and technology (software engineering, UX research and design, and data science), business (sales, marketing, communications, and HR), and BOLD, which stands for Build Opportunities for Leadership and Development—an internship program for undergraduate seniors from historically underrepresented backgrounds. Internships are typically full-time, paid, and run for 12-14 weeks during the summer.
Like other major tech companies, Google’s internships give interns the opportunity to work on projects that will see the light of day, whether they’re public-facing products and services, or tools designed to be used in-house. The company also pairs interns with mentors and managers, makes accessible additional learning and development programs, and those who perform well are often considered for a permanent full-time position.
The responsibilities of a data science intern at Google will vary depending on the team they join and the project they’ve been assigned. Across the board, though, data science interns are expected to be familiar with programming languages such as SQL, Java, C++, or MATLAB, and to have a background in or be studying Statistics, Applied Mathematics, Computer Science, or a related technical field. It also helps to have experience in or knowledge of data gathering, cleaning up complex data sets, business analytics, gleaning insights from big data, and an interest in working on Google products.
With a sufficient technical foundation, Google’s data science interns are thrust into the deep end and work on real-world projects. The company’s interns have helped launch AdSense features—the website monetization tool used by more than 11 million websites and generates billions of dollars in annual revenue; they’ve built a notifications viewer, which helps Google’s internal Billing team engineers manage activity in customer accounts; they’ve worked on how to make Google Assistant better for people with visual impairments; and they’ve created new tools to help parents monitor their kids’ device usage.
In a nutshell, Google’s data science interns are considered part of the team and are expected to contribute both their technical skills and creative problem-solving to whatever products, services, or projects the company throws their way. They are also expected to collaborate with a wide variety of people, from fellow interns to seasoned employees across different teams to see their projects through completion.
Landing an internship at Googles requires showing the application reviewers that you have both the technical chops to handle database querying challenges and the right attitude, or “Googleyness”, to thrive at one of the most innovative companies in the world.“Are you intellectually curious? Do you work well in an ambiguous environment? Do you get excited by tackling a really big problem?” said Kyle Ewing, director of talent and outreach programs in Google’s People Operations Department. “That is the kind of person we know is the most successful here.”Below are steps to follow that can bring you closer to a data science internship at Google.
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. 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 online course.
Some of Google’s data science internships require that a candidate be currently enrolled in a degree program in Computer Science, Statistics, Applied Mathematics, Economics, or Physics. Some internship roles—particularly those related to machine learning—require a Ph.D. or other preferred qualifications in Deep Learning, Computer Vision, Biostatistics, and Advanced Analytical Methods.
It’s important to align your skills with the requirements of the job—if you have a skills gap, work on filling it in.
The résumé is the first thing that Google’s hiring team will see of a candidate. The company’s own careers page advises that candidates use their CV to highlight how their skills align with the internship they’re applying for and provide specific examples of project successes. Candidates should also include on the CV their GPA, college transcript (unofficial is fine), and any relevant coursework or projects that demonstrate their skills and experience. It’s best to keep the CV to one page.
If the company’s hiring team is impressed with your CV, they may then ask to see your portfolio. This is an opportunity for you to show off your leadership skills, your grasp of the quantitative discipline, and any technical experience you have with statistical software, experimental design, sampling methods, statistical data analysis, multivariate analysis, and creative problem-solving.
Hiring managers are looking for experience from either former internships or personal projects that show off role-related knowledge and leadership skills.
“This does not mean you have to have managed people,” Ewing said. “But what kind of immersion leadership have you demonstrated and what kind of initiative have you taken on campus?”
When choosing between applicants, Google considers a person’s “Googleyness,” which is a reflection of an individual’s personality.
“How easy are you to get along with?” said Kevin Miller, who previously worked on Google’s AdWords. In summing up Google’s recruiting process, he said that the company measures “Googleness” by asking themselves whether they would want to work with the candidate every single day. “Would you be happy if you sat next to this person every single day? Would you be able to do good work, and would you enjoy their company?”
This means that in addition to brushing up on your technical skills, you need to invest just as much in your communication and interpersonal skills.
If you make it to the interview stage, the next step involves a series of interviews over the phone, via video conference, or in-person in Mountain View, New York, or at one of the company’s other campuses to assess your skills.
For a data science internship, you can expect to be asked technical questions for which you will need to code either on a whiteboard, in Google Docs, or over the phone. Google advises that it’s important to show the hiring manager how you arrived at your solution, so be sure to structure your responses in a way that shows your work, and think aloud.
“We look at general cognitive ability,” said Ewing. “How do you unpack and tackle these large problems that exist and distill them down to something you can take hold of?”
In addition to showing that you understand technical concepts like linear models or quantitative analysis of data, some of the behavioral questions candidates should prepare for include: “How do you work best, both as an individual and as part of a team?”, “What challenges have you faced at school or at work and how did you overcome them?”, and “Which of your skills or experiences would be assets in the role and why?”
Google interns in the United States are among the most well-compensated of any internet company, with Glassdoor reporting that Google interns are paid around $7,500/month.
In addition to generous compensation, a data science intern at Google receives a signing bonus, housing stipend, coverage for any travel expenses related to moving for the summer, and health, dental, and eye insurance for the duration of their internship.
The experience of being a data science intern varies depending on the team with which an intern works. But both current and former interns have said that Google’s internships take them seriously as professionals.
Instead of fetching coffee, taking lunch orders, or photocopying, data science interns can expect to perform data analytics, work with big datasets, and on some projects serve as the team’s quantitative analyst. At the completion of the internship, those who do well are often invited to return the following year or are offered a full-time role.
“I am actually seeing that I am impacting the business and my role isn’t just to sit here for 11 weeks,” said Cedoni Francis, a 2019 Google intern. “With this program, you are a full-time employee and are expected to produce work as such even though you’re an intern.”
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