Data Scientists Salary: How Much More Can You Make?

What’s the average data scientist salary? As you might expect, those with the right combination of data-science skills and experience can earn quite a bit—especially if they’re in a position to advise a company’s senior management on strategy. Let’s break it all down, but before we do, let’s take a moment to trace out what a data scientist actually does.

Data scientists play a vital strategic role at the companies that employ them. They’re often tasked with mining their firm’s data for strategic insights that CEOs, CTOs, and other executives can use to plot a longer-term roadmap. No wonder it’s a notably fast-growing profession. Although the term ‘data scientist’ is often used interchangeably with ‘data analyst,’ it’s important to note that those roles technically aren’t the same; data analysts often focus on much more tactical problems than data scientists. 

Folks who began their careers as analysts, developers, economists, and mathematicians often fall in love with data to the point where they opt to become data scientists. Fortunately, there are a variety of career paths that will land someone in a data scientist role; the following jobs often feed right into data science:

What is a data scientist’s starting salary?

Last year, as part of a comprehensive survey of the data-science industry, we analyzed Dice’s database to figure out the salary numbers for various data scientist roles. At the same time, we calculated the average length of time that a data scientist spends in each role. As you can see from the chart, junior and associate data scientists (basically, those just starting out) can earn quite a bit over entry-level jobs in other professions.

As data scientists climb the ranks (and obtain more specialized skills), their salaries increase rapidly. An A.I./machine learning engineer with data-science skills can expect to pull down compensation comfortably in the six-figure range, for instance. Length of tenure also a huge factor, as you can see from this analysis of data from Burning Glass, which collects and analyzes millions of job postings from across the country:

For those debating whether to enter the data science arena, this data is good news: Even those with relatively little experience can pull down pretty solid salaries relative to other tech roles. Climbing the career ladder, though, will hinge on keeping your skills current—especially given the number of people entering the arena on a yearly basis.

According to Burning Glass, the specialized skills that will allow you to advance within the data-science community include the following; as you can see (and might expect), there’s a heavy emphasis on analytics:

What is a data scientist’s average salary? 

According to Burning Glass, the median salary for a data scientist is $112,774. As we’ve broken down above, though, there are a number of factors that can lead that to rise considerably. For example, data scientist education/training/certifications have an impact on how much you can earn:

Where do data scientists make the most money?  

Data scientist jobs demand (and salary) varies by state; as you can see below, California and New York lead the pack when it comes to time-to-fill and overall salary. Both of those states are economic powerhouses with more than enough companies monetized enough to hire expensive data scientists. 

However, other states are no slouch when it comes to paying data scientists. Texas, Virginia, Illinois, Georgia, and other states all paid out median six-figure salaries:

Are data scientists in demand?  

Burning Glass suggests that, as a profession, data scientist jobs will grow 19 percent over the next 10 years. Right now, the average time to fill an open data scientist position is 44 days, indicating a high level of demand; that’s quite a long time for employers to search for an open candidate.

However, companies won’t hire just anyone for an open data-science slot. Over the past few years, data science’s increasing popularity has lured more people to the field. In turn, that’s led some analysts to announce a glut in the market. For example, a blog posting by Vicky Boykis, senior manager for data science and engineering at CapTech Ventures, suggested there might actually be an oversupply of entry-level talent.  

“Based on my own participation as a resume screener, mentor to data scientists leaving boot camps, interviewer, interviewee, and from conversations with friends and colleagues in similar positions,” Boykis wrote, “I’ve developed an intuition that the number of candidates per any given data science position, particularly at the entry level, has grown from 20 or so per slot, to 100 or more.”

An analysis of Dice data, meanwhile, suggests that employers are demanding data scientists at a slower rate than between 2016 and 2018, when job postings for the profession spiked. If the market’s indeed becoming more saturated, that changes the game for data scientists: The emphasis is now on skills mastery and specialization, which allow professionals to truly stand out from the crowd. There’s always demand for those with highly specialized abilities. 

What’s the best way to secure a high salary as a data scientist? Being prepared as possible for applying and interviewing for a job. Check out Dice’s other helpful resources that will help you secure your next role:

Structure your resume the right way with our data scientist resume example.

Ace your next interview by knowing the top data scientist interview questions and answers.

Download Dice’s 2022 Salary Survey Report Now!

6 Responses to “Data Scientists Salary: How Much More Can You Make?”

  1. Clearly not written by someone with experience in data science. The data analysis here lacks any domain understanding to the points that it is laughable.