BY Meghan MalasMay 11, 2022, 1:44 p.m.
An attendee demonstrates software at AWS re:Invent 2021, a conference hosted by Amazon Web Services, at The Venetian Las Vegas, as seen November 2021 in Las Vegas, Nevada. (Photo by Noah Berger/Getty Images for Amazon Web Services)
Data scientists have been in high demand for several years as some of the world’s largest technology companies seek to maximize the power of data-driven strategies. Data scientist salaries reflect this demand; the job has a median base salary of $120,000 and more than 10,000 job openings, according to numbers from Glassdoor’s Top Jobs list.
Companies like Amazon Web Services (AWS) are hiring a growing number of data science and machine learning graduates for Amazon’s Machine Learning Solutions Lab team, says Antonia Schulze, data scientist at AWS. And more graduates of data science degree programs are likely to be hired as more universities offer specialized data science programs, Schulze says.
At AWS, at least, it’s more common for data scientists to have degrees in computer science and math or statistics. And while education is key, there are other qualities besides a specific degree that are important for data scientists in Big Tech.
Fortune spoke with three experts from AWS, Netflix and Meta to learn how to become a data scientist at a major tech company.
Big Tech Companies Prefer Applicants with Masters in Data Science
In the last decade alone, MIT, University of California at Berkeley, New York University and Yale University are among the schools that have established dedicated centers, institutes, departments and divisions to data science. This indicates that higher education institutions see a need for more specialized programs to prepare graduates for the field.
Specific technical knowledge is required 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 technical skills, knowledge of programming, especially R and Python, is essential,” says Schulze. “However, a basic understanding of the mathematical concepts supporting data science and machine learning models is also a must.”
The majority of Netflix data scientists have a master’s or doctorate. in a field like statistics, machine learning, economics or physics, says Stone. These types of degree programs provide students with the technical skills in data analysis, machine learning, statistics, or causal inference that Netflix requires of its data scientists. Meta requires all applicants for data science positions to have a bachelor’s degree in math, statistics, or a relevant technical field. A master’s or doctoral degree. in a quantitative field is also a preferred qualification at Meta.
But while an advanced degree can provide the upskilling you need to get a job at AWS, that’s not all. “An academic structure can certainly help in the way we approach scientific problems, but all of this can also be learned on the job,” says Schulze.
Big tech companies prioritize quality over quantity for work experience
“While we often see applicants with advanced degrees applying, what interests us just as much or more is previous work experience,” says Stone.
At Netflix, while a strong technical foundation is necessary, it’s also important for data scientists to be creative in how they use data to drive better business outcomes. Additionally, for some data roles, expertise in the field of entertainment and studio production may be required. At Meta, data scientists must demonstrate experience measuring the success of product efforts, as well as an ability to forecast key product metrics to understand trends.
But you don’t necessarily need years of experience in the field to land a data science job at a Big Tech company. The professionals on the data science teams at Netflix and AWS have between a few years and several decades of professional experience before joining.
“When I graduated, I joined Amazon’s operations team as a business intelligence and data science intern,” Schulze says. “At the end of my internship in 2019, I had the opportunity to join AWS as a data scientist with the Machine Learning Solutions Lab and I have been part of the same team since my arrival full time.”
Successful big tech data scientists are dynamic, connect data to the big picture
“Executives provide the context for business priorities and strategy, but individual contributors such as data scientists determine most of the details on both the ‘what’ and the ‘how’,” says Stone. Fortune. Netflix’s team has grown steadily over time and now includes data scientists, data engineers, data analysts, and consumer researchers.
This collaboration relies on team members with strong communication skills. In companies like AWS, Netflix, and Meta, data scientists need to be able to effectively share information and insights with other stakeholders, including people without a technical background. Data science is a rapidly evolving field. Technology companies are therefore looking for employees who can translate data into business impact without a predefined roadmap.
“In order to grow and thrive in this evolving scientific space, data scientists must enjoy learning and constantly researching new topics,” says Schulze.
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