Data science is one of the hottest jobs currently out there. And I’m not just saying that because I’m a data scientist myself and have previously written content on the data science job market and how to break into it (shameless plugs). The numbers - and any self-identifying data person has to respect the data - speak for themselves.

*Source:* *BLS Employment Projections, interpolation of 2022-2032 projection*

According to the BLS, there is an expected 35% increase in the employment level of data scientists between 2022 and 2032. Compared to an overall projected employment growth of 2.8%, this is significantly higher growth. Even compared to similar data-focused jobs, data scientists frequently come out on the top end of job growth forecasts (more on this later).

In this post, I would like to take a deeper dive into the data science job market and provide a holistic overview of where the opportunities and roadblocks may lay. There is a lot of speculation surrounding the current state of data science - given the mass layoffs in tech recently - and hype for the immense potential for job growth in this relatively new field. New developments in AI and analytical methods, as well as the constantly evolving scope of what exactly the role of a data scientist is, bring further uncertainty. My hope is to cut through these questions and developments that may affect the data science field and shed some light on the forecasts of the job market.

Note: To keep the scope of this already broad article in check, I’m going to focus on the US job market. Apologies to my international data scientist colleagues - I hope to write a future post that will encompass the global job market!

Supply of Data Scientists

As we saw in the first chart, as of 2022 there were an estimated 168,900 data scientists employed in the US. While data scientists have a presence in every industry category in the BLS - reflecting the pervasive nature of data tasks in the modern economy - they are highly concentrated in the Professional Services, Financial, and Information sectors. These three industries together account for 62.6% of data scientists, while the following industries all have less than 1,000 data scientists in total: Real Estate, Utilities, Construction, Arts-entertainment-recreation, and Mining-quarrying-oil-gas-extraction.

Looking forward, among detailed industry categorizations, the industries expected to have the highest employment growth of data scientists are Computer systems design, Management-scientific-technical-consulting services, and Insurance carriers.

*Source:* *BLS Employment Projections, filtered to Display Level=4*

The additional 32,900 data scientists expected to be hired by these top 10 industries account for 55% of the total expected employment increase (+59,400) in the next ten years. These ten industries also account for 53% of total employment for data scientists today. If you’re looking to maximize your chances of employment in the next few years as a data scientist, besides the obvious of applying to tech sector companies, I would recommend looking into the professional sciences and finance industries.

One other way to measure the supply of data scientists is to measure Google Search traffic of data science-related terms. While this is a crude measure that mostly captures interest and volume of data science mentions, it does provide further evidence of the growing interest in the field.

To hammer home how popular data science is becoming, we can look at search traffic for “Data Scientist” relative to other related industries such as software engineering and computer science. Here we see data science fairing well - somewhat overshadowed by even larger explosions in searches for software engineer and data analyst (though there is likely a large amount of cross-traffic between these two terms), but holding its own and in fact being more searched than data engineer and computer scientist.

Zooming in on just the data science trend, we also see that searches for jobs, salary, and masters in data science have all greatly picked up since 2014. There was a substantial drop in 2020-2021, as the COVID pandemic overwhelmed all else, but the overall trend for the past decade is a clear and mostly consistent upward movement. Searches for jobs and masters also show no sign of slowing down, perhaps indicating continued momentum in interest for entering the field by newcomers.

Demand for Data Scientists

Those industry splits we saw earlier of where data scientists are currently employed probably aren’t surprising anyone, as we don’t often think of a computer nerd, data-focused person working at a construction site or art museum. More interestingly, perhaps, is where data scientists will be most in demand looking forward. Here too, however, we see stability - the concentration of data scientists by industry is expected to remain more or less the same through 2023. Looking at the 2032 projected industry breakdown, no industry gains or loses more than 0.7% of its 2022 share of the data science occupation.

The growth in employment level by industry basically mirrors the current distribution, meaning that there will be the most job openings in the industries currently with the most data scientists already. So while data science employment is expected to continue taking off, that hiring will likely be in industries already heavily hiring data scientists.

Perhaps more interesting is the employment percent change by industry, showing which industries are forecasted to hire the most data scientists relative to their current employment level of data scientists. While we still see many of the same industries leading the pack, there are some newcomers at the top of the rankings - Transportation and Administrative Services are projected to hire disproportionally more data scientists compared to their current employment share, sitting near the top of the employment percent change list. This may reflect increasing demand for data scientists in these industries, or may just be a reflection of above-average growth in the industries themselves.

However, to put the growth of data science jobs into perspective, we need to compare this growth to other occupations. As I mentioned before, data scientists are at the top end of job growth compared to related jobs. Take, for instance, the growth of all the detailed occupations within the “Mathematical science occupations” group, of which data science is a part:

Whether we look at employment growth by level or by percent (to account for data science already being a larger field than these related occupations), data scientists come out on top. Okay, but what about other occupations besides mathematical sciences - which is admittedly a very small portion of the overall job market.

Including the entire universe of detailed occupations, we see that data science still ranks as the 3rd highest occupation for employment growth over the next decade. No matter how you slice it, the job growth for this field is expected to be among the very top, competing with specialized technical workers such as wind turbine service technicians and broad swaths of the labor market like nurse practitioners. Also of note, ranked right below data scientists are Statisticians, a closely related occupation with a very transferable skillset to data science. For those who know how to work with numbers and apply such expertise in the real world, the future of the labor market is looking very, very bright.

*Source:* *BLS Occupational Employment and Wages, May 2022*

To wrap up this post, I lastly want to cover how much one can expect to earn as a data scientist. Here, again, the prospects are very bright. Nationwide, data scientists were earning a $103,500 median annual wage as of May 2022. This ranges as high as a $147,390 mean annual wage in California, and $133,990 in Virginia, which both employ some of the highest numbers of data scientists. Note that this annual wage is simply based on the hourly earnings rate, and thus does not include bonuses or equity offerings that are common in the fields data scientists tend to be hired in (finance, technology, and professional services). Compared to the $61,900 annual mean wage for all workers in May 2022, we can confidently say that data scientists are doing well for themselves.

Final Notes

If this post has you thinking about applying to be a data scientist, check out my educational article on how to break into data science (written for my nonprofit, Menti).

All charts and data visualizations you see in this post were created by me, using the following packages in R: readxl, dplyr, ggplot2, ggthemes, RColorBrewer, reshape, scales, usmap.

If you have questions or constructive feedback, feel free to email me at troded24@gmail.com, submit an inquiry on this website, or leave a comment on this post! Thanks for reading.