If you’re looking for a growth field, it’s hard to beat data science. Glassdoor named data scientist the third-best job in America in 2020 (after awarding it the top spot in each of the four previous years). The Harvard Business Review declared data scientist the sexiest job of the 21st century, also noting that “the shortage of data scientists is becoming a serious constraint in some sectors.”
Quanthub agrees: data science faces a significant talent shortage, creating a seller’s market for capable data scientists marketing their skills. What employers seek from data scientists in terms of education and skill sets—and what they’ll offer in compensation—naturally varies by location and industry. You’ll find data science jobs listed under various titles, including:
Navigating the data science job market can be like sifting through raw data: it’s not always cleanly packaged and easy to understand. This article on Data Science Jobs: Who’s Hiring + How Much Do They Pay digs into the data to address these questions:
Data science professionals organize and interpret data; it’s difficult to define the field any more precisely because data science careers are so varied. Data scientists frequently hold senior positions managing data mining and data interpretation operations at universities, hospitals, nonprofits, private businesses, and other enterprises.
Many data science professionals specialize in one or more aspects of the data chain, such as:
Someone with a data analytics background may focus on interpreting data sets. In contrast, a machine learning expert might specialize in developing effective data gathering systems. Data science has many applications across functions and industries.
Harvard Business Review separates data scientist jobs not by title, but type. Their categories:
While there are also full-stack data scientists who do both, larger companies often divide these roles even further. For example, you may specialize in data infrastructure—keeping systems at peak operation for others to use—or data quality and governance—essentially quality assurance and security.
According to the United States Bureau of Labor Statistics (BLS), the ten-year growth rate (2019-2029) for computer and information research scientists is 15 percent, more than three times the growth rate of the American labor market. Current data show that half of data science companies haven’t suffered during the pandemic—and some of them have even grown.
The title ‘data scientist’ frequently appears atop lists of the hottest jobs. Data scientists and mathematical sciences professionals earn a median income of $100,560 per year, according to the BLS.
Education plays a huge role in the jobs available to you. Data scientists with bachelor’s degrees won’t qualify for as many positions as those with advanced degrees in data science (master’s or doctoral).
Many data science positions require a bachelor’s degree or the equivalent at bare minimum. It’s essential for those who want to become data scientists to know at least one programming language—usually Python, R, or SQL.
Even entry-level positions in this field can require work experience. Early careers in data science include:
These jobs aren’t exclusively entry-level. Experienced data analysts take on more responsibility and higher pay. For “freshers,” it’s important to look for prefixes like “entry-level” or “junior.”
You may be wondering how it’s possible to get experience without having a job. The best way is through internships, which often pay well and are extremely competitive. Master’s students frequently fill the best internships, but there are good opportunities for undergraduates, too.
According to an article on the Rutgers University – New Brunswick Career Development Center website: “Data scientist positions at top tech companies allow for more specialization in a niche area and can also provide a great training ground, as many hire for internships and new grad positions.” It’s rare to start as a data scientist unless you have a master’s degree, so many new bachelor’s degree graduates begin as analysts.
Let’s say you don’t have a degree or majored in something else. Most data science jobs, except basic data entry positions, require training. The good news: self-education counts.
While those who transition into data science often go back to school, they can also complete boot camps or teach themselves. Self-taught data scientists can go far in the business, although higher education is usually necessary for top positions.
It’s quite difficult to get a data science job with zero experience whatsoever. Those without professional expertise commonly showcase their skills through personal projects by building a portfolio for prospective hiring managers. This is a common practice throughout the industry but especially important for those without formal training. Some data scientists then begin freelancing, often through sites like Upwork. Again, you probably need work samples.
Data science professionals can use their knowledge and skills in many ways and in almost every industry. You might specialize in business intelligence or robotics or healthcare informatics. There are almost too many options.
90 percent of data scientists hold master’s degrees, and 47 percent hold doctoral degrees. ( )
The Bureau of Labor Statistics sets median data scientist annual pay at just over $100,000. Top-paying sectors include ( ):
- Computer and peripheral equipment manufacturing ($148,290)
- Semiconductor and other electronic equipment manufacturing ($142,150)
- Specialized information services ($139,600)
- Data processing, hosting, and related services ($126,160)
- Accounting, tax preparation, bookkeeping, payroll services ($124,440)
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You don’t technically need a master’s degree to get a data science job, but the odds are much more in your favor when you do. According to a KD Nuggets survey, 88 percent of data scientists hold a master’s degree or higher. Nearly half—46 percent, more precisely—have PhDs. Other sources report similar figures.
If you decide to earn an advanced degree, you should consider factors like affordability and specialization. For example, focusing on data architecture may lead to better career prospects than an analytics concentration.
Schools with Master of Science or PhD in data science programs (often both) include:
It’s possible to work in data science without a degree, but having more education improves your odds. Most people don’t just take a weekend bootcamp and jump into an executive position.
A few schools offer a two-year associate’s degree in data science. But, rather than prepare you specifically for jobs, these degrees focus more on helping students transition into a bachelor’s degree program.
A bachelor’s in data science prepares graduates for entry-level positions—usually as an analyst or low-level data scientist. Other careers for those with a bachelor’s in data science include data architect and information officer.
Those with a Master of Science (MS) in Data Science have more career options, including
Many of these jobs can also be earned with a degree in data analytics and other closely related subjects.
A doctoral degree is the highest level of education available. Earning a PhD in data science can prepare you for several career paths in academics, research, and/or government. For those who choose the private sector, PhDs can help qualify you for c-suite or department leadership positions.
PhD holders compete for some of the same jobs as master’s degree-holders, like high-level machine learning or data scientist positions. In these instances, having a doctorate is usually an advantage.
According to the University of Wisconsin Extension, “The more a data science professional engages in managerial tasks—such as leading team projects, identifying business problems to be solved with analytics, or communicating with external parties—the higher the salary.” Education, location, and company are other factors that impact pay.
These factors can equate to huge salary swings. Computer and information research scientists may earn a median income of $122,840 per year, but the range goes from under $70,000 to over $190,000. Big data engineers earn between $70,000 and $115,000 per year at the junior or generalist level to $100,000 to $165,000 at the expert designation. A data science or analytics manager usually earns between $90,000 and $140,000—though you may start out as a data analyst earning closer to $60,000.
There isn’t a consensus on which data science positions pays the most all the time, though, at an average annual salary of nearly $180,000, chief data officer is a good bet for the top slot.
The best way to find a part-time data science jobs is through a career service like ZipRecruiter. Still, freelancing is the best way to set your own hours. Data scientists who go this route often get work through freelance platforms or contacts from old jobs.
It should go without saying that it’s impossible to completely answer this question without accounting for personal preferences. Not wanting to move your family and hating New York City are two perfectly valid reasons for not taking an offer at an otherwise great company. Working at a small business, or for yourself, may be more valuable for some. Finally, great data science jobs exist outside the corporate structure; in the government, for instance.
That said, here are (generally) the most desirable data science jobs in the country:
Google is the gold standard for employee relations. It’s the kind of environment you’d see in a movie, except it’s real. Employees are paid well, fed, and even have places to exercise. The company has offices in New York, San Francisco, San Diego, Colorado, and Canada.
A lot has been written about working conditions in Amazon warehouses, but like most places, it’s a good corporate gig if you like a competitive environment. The company offers excellent benefits, and the upper reaches of the pay range hit $150,000 per year. Employees can work in American cities, such as Washington and New York, or internationally, in England and India.
According to Diffbot, Amazon has 1,846 data science positions, including 694 data engineers and 184 database administrators.
LinkedIn’s work environment has a steller reputation. By all accounts, employees enjoy working there.
Though not as large as some of the other companies on this list—they have offices in England and India, as well as major US cities—LinkedIn has a deep focus on data science. Data professionals work in one of four channels:
As of 2019, Microsoft employed 1,800 data science professionals—including 128 artificial intelligence professionals, although the staff is predominantly data engineers and scientists. One of the first major tech companies, Microsoft is still considered an excellent place to work. The company offers interesting projects and great compensation. On the downside, many employees feel overworked and deal with bureaucratic issues.
Apple has more than 500 data science positions, which is a lot, but not compared to some other major companies. Still, employees are paid very well. Software engineers at Apple earn an average annual salary of over $150,000, according to Indeed.
The corporate culture gets mixed reviews, with some calling it too constricting and marketing-focused. Still, working at Apple looks great on a resume and delivers no shortage of interesting projects.
More than 2,500 data scientists work at IBM—more than any other company. They employ 1,111 database administrators alone. Employees at IBM are often able to work from home and feel satisfied with their work-life balance.
Oracle is one of the biggest data companies globally, even though it may not be a household name (for laypeople) on the level of Google or Apple. The company employs over 1,200 data professionals, more than 800 of whom are database administrators. Like all major tech companies, Oracle offers competitive pay, perks, and benefits. One main criticism of Oracle is that the company struggles to innovate.
Like Oracle, Facebook employs over 1,200 data science professionals, primarily as data scientists and data engineers. There are also over 60 machine learning engineers in the company.
Once the pinnacle of tech culture, Facebook has come under fire in recent years—to put it lightly. Beyond personal data misuse and election interference allegations, stories from former employees have soured public perception. It’s still considered one of the top places to work.
Though Silicon Valley gets all the headlines, there are excellent data science jobs in government. Government salaries are usually similar to the private sector, but you’ll earn raises on the federal pay scale, aka the General Schedule (GS). Federal employees also earn excellent benefits.
The FBI has a few data positions, including:
These professionals use data science to stop crime, including cyber offenses and terrorism. According to Special Agent Avatar LeFevre, who is unit chief of the STEM division, the main difference between a major company and the FBI is “not working to improve the bottom line, to get the stock higher; we’re working to defend the American people.”
According to NASA, its “data scientists are helping to manage and make sense of this influx of data to drive business decisions and answer pressing questions about machine learning, astronomy, aviation and more.”
Like other agencies, the NSA needs data science professionals, though some positions may require a more general computer science background. Broadly, the NSA works to ensure information is transmitted safely and tries to intercept counterterror measures. Those with a data science background can get roles like:
Everybody is trying to make better use of data, and the military is no different. The Department of Defense has put a higher premium on using data to make intelligent decisions, including creating a data science division at the Office of People Analytics, which focuses on building new algorithms and techniques to optimize data processing.
Though it doesn’t have a specific building a data science division, the Navy acknowledged a need for data science professionals like statisticians and data scientists in 2019. Some other data jobs that may be instituted include:
You don’t need to be a service member to become an Army Cyber Officer, a reserve position. According to the Army, “A Data & Analysis Center Army civilian employee receives a comprehensive compensation package as well as the option of a flexible work schedule.”
According to the Army talent management website, top candidates often have employment backgrounds like:
There are excellent data science jobs worldwide, not just in the major American cities that people associate with tech. Plus, working remotely has become a popular alternative. Still, some cities attract more data professionals than others. Since job titles don’t really change, this list focuses on each city’s overall market.
Atlanta has become an increasingly popular option for data scientists in the past few years. The median salary ($114,300) for these professionals is slightly below the national median. But, the cost of living in Atlanta is one percent below national average, which is not something that most of the other top cities for data science can say.
Austin has a thriving data scene. The University of Texas at Austin recently became home to the The National Science Foundation’s AI Institute for Foundations of Machine Learning, and there are many tech startups.
With over 100 big data companies in the city,
Boston is a great place for data science. There are countless networking conferences and continuing education opportunities in and around town. The median salary for computer and information research scientists in Boston is slightly lower than average, but still quite high at around $115,000.
This too-often-overlooked city on the East Coast is quickly becoming a leader in the tech and banking industries. More companies are moving to the Charlotte area, creating an abundance of job openings.
Though not always included in lists of best cities for data scientists, Chicago is a major hub. Data science professionals here earn around the national median, just over $120,000, and Chicago is considered one of the best cities in the country.
Austin might get more press, but Dallas is also a great city for data science. Nearly two dozen Fortune 500 companies have offices there. Data, computer, and information research scientists earn about $15,000 above the national median.
While not quite reaching the heights of New York or San Francisco yet, Denver has established itself as a great spot for data scientists. The extensive data analysis company Palantir recently moved there, and others are expanding into Colorado. The state offers a beautiful natural landscape and low living cost (compared to other major cities).
Houston has the third-highest salary for data scientists of any city after adjusting for cost of living, according to a 2018 TechRepublic study. You may make more in New York, but you’ll keep more in Houston.
Though not a considered data science hub, Kansas City has its share of tech companies. A LinkedIn report recently showed 210 available data science jobs in the Kansas City, MO area. Computer information research scientists earn well below the national median here, which is still slightly over six figures.
Las Vegas has interesting data jobs, especially if you want to work in casinos, which are leaning more on data than ever before. According to Glassdoor, data scientists in Las Vegas earn an average annual income of $96,241, not including bonuses and other incentives.
Most California’s data jobs are in cities like San Francisco, but major companies in LA also offer positions to data scientists. The Los Angeles area pays computer and information research scientists a median income of $129,000, slightly above national numbers, though you need to deal with high living costs as well.
NYC is one of the best cities for data science. The city is home to thousands of companies offering numerous opportunities for young professionals. New York computer and information research scientists earn a median of $132,160, though the downside is the city is very expensive.
Thanks to companies like Intel and Nike, Portland attracts many data scientists. The tech district is even nicknamed Silicon Forest. The median salary in Portland is slightly below national figures, but not by much.
There are a few big data companies in the city, such as Amdocs, and data scientists here comfortably earn six figures. While St. Louis isn’t a huge data science draw at the moment, it’s a great place to work and live.
San Diego is a tech hub—the industry has grown by nearly 20 percent from 2017 to 2020, which means there are data science jobs available. Professionals here command a median salary of nearly $126,000, and it’s just a beautiful place to live.
It goes almost without saying that San Francisco is the best city for tech—the basketball team’s stadium even used to be called Oracle Arena! The median salary there is a whopping $142,740, though you need to deal with high living costs. Still, there are more opportunities in San Francisco than anywhere else.
Home to Amazon and offices of major companies like Google, Seattle is a great city for data science—and rain. Computer and information research scientists earn a $144,000 median pay, which is well above average.
The nation’s capital has one of the lowest costs of living among top cities for data science, less than one percent above the national average. It’s also home to the US government, an enormous employer of data scientists. Finally, there are excellent data science programs at area schools like University of Virginia.
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