How to become a data scientist at Big Tech

by Megan MallasMay 11, 2022, 1:44 pm

An attendee demonstrates the program during AWS re: Invent 2021, a conference hosted by Amazon Web Services, at The Venetian Las Vegas, as seen in November 2021 in Las Vegas, Nevada. (Photo by Noah Berger/Getty Images for Amazon Web Services)

Data scientists have been in high demand over the past several years, as some of the world’s largest technology companies seek to maximize the power of data-driven strategies. Data scientists salaries reflect this demand; The job has a median base salary of $120,000, and more than 10,000 jobs, according to figures from Glassdoor’s Top Jobs list.

Companies like Amazon Web Services (AWS) are hiring an increasing number of graduates with degrees in data science and machine learning for the Amazon Machine Learning Solutions Lab team, says Antonia Schulze, data scientist at AWS. Schulz explains that more data science degree program graduates are likely to be hired as an increasing number of universities offer data science programs.

On AWS, at least, it’s common for data scientists to have degrees in computer science, mathematics, or statistics. And while education is a key component, there are other qualities besides a certain degree that are important to data scientists at Big Tech.

luck I spoke with three experts at AWS, Netflix, and Meta to learn how to become a data scientist at Big Tech.

Big tech companies prefer applicants with a master’s degree in data science

In the past decade alone, MIT, UC Berkeley, New York University, and Yale University have been among the schools that have created dedicated data science centers, institutes, departments, and divisions. This is an indication that higher education institutions see a need for more specialized programs to prepare graduates for this field.

Specific technical knowledge is needed to become a data scientist, and a master’s degree in a quantitative field – although not always required – is a good way to upgrade your skills.

“In terms of hard skills, programming knowledge – specifically R and Python – is essential,” says Schulze. “However, a basic understanding of the mathematical concepts that underpin data science and machine learning models is also essential.”

The majority of data scientists at Netflix have a master’s or doctoral degree. In a field such as statistics, machine learning, economics, or physics, says Stone. These types of degree programs provide students with the technical skills in data analytics, machine learning, statistics, or causal reasoning that Netflix requires of data scientists. Meta requires all applicants to data science roles to have a bachelor’s degree in mathematics, statistics, or a related technical field. Master’s or Ph.D. In the quantitative field it is a preferred qualification in Meta as well.

But while an advanced degree may provide the skills you need to land a job at AWS, it is not all. “Academic structure can certainly help with the way we approach scientific problems, however, all of that can be learned on the job as well,” Schulze says.

Big tech companies prioritize quality over quantity of work experience

“While we often see candidates with advanced degrees apply, what we are more or less interested in is prior work experience,” Stone says.

At Netflix, while a strong technical foundation is necessary, it is also important for data scientists to be creative in how they use data to achieve better business outcomes. Additionally, for some data roles, experience in entertainment and studio production may be required. In Meta, data scientists need to demonstrate their expertise in measuring the success of product efforts, as well as the ability to predict key product metrics to understand trends.

But you don’t necessarily need several years of experience in this field to land a data science job at Big Tech. Professionals in the data science teams at Netflix and AWS have two years to decades of work experience prior to joining.

“When I graduated, I joined the Amazon operations team as an intern in business intelligence and data science,” Schulz says. “Upon completion of my internship in 2019, I had the opportunity to join AWS as a data scientist in the Machine Learning Solutions Lab, and have been with the same team since joining full time.”

Successful Big Tech Data Scientists are dynamic, connecting data to the big picture

“Leaders give context to the business’ priorities and strategy, but individual contributors such as data scientists drive most of the detail around the ‘what’ and ‘how’,” Stone says. luck. The Netflix team has grown steadily over time and now includes collaborating data scientists, data engineers, data analysts and consumer researchers..

This collaboration relies on team members who have strong communication skills. At companies like AWS, Netflix, and Meta, data scientists need to be able to effectively share information and ideas with other stakeholders, including people without technical backgrounds. Data science is a rapidly developing field, so technology companies are looking for employees with the ability to translate data to business impact without a predetermined roadmap.

“In order to grow and thrive in this cutting-edge science space, data scientists need to enjoy learning and constantly research new topics,” Schulz says.

Find out how the schools you’re considering made it to the Fortune ranking of the best master’s in public health programs, business analytics programs, data science programs, part-time, executive, full-time, and online MBA programs.

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