Patrick Harrington, Ph.D. — Co Founder and Chief Data Scientist, Paysa
The 1851 battle-cry of American westward expansion, “Go west, young man and grow up with this country” appears to be alive and well when discussing economic opportunity for software engineers and their related fields.
As America continues to tip heavily away from manufacturing and older, low-skilled industries (see Figure 1.), the services industry, in particular software engineering and its related professions, e.g., data scientists and product managers, continue to churn out incredibly high paying jobs with incredibly rosy career prospects.
In the years following the “great recession”, the exacerbation of “like” attracting “like” appears to have accelerated. Specifically, the communities and metropolitan areas in which these software engineering type professionals are packing their bags and moving to these tech havens.
Here at Paysa, we are able to mine through 90M professional resumes of individuals working and living in America. Couple that with over 30M individual level compensation data points and you can understand at the most granular levels how professionals are moving throughout their career but also where and how much they earn. Throughout this piece, we are following 5.8M software engineering professionals throughout their career upon making a job change to a new locality, e.g., Detroit to San Francisco.
So in the years of 2010 forward, one interesting question that is near and dear to our hearts are where are these software engineers folks moving to and what regions of the country desperately need to revaluate their offering to keep these highly educated, highly paid entrepreneurs in their communities.
No other metropolitan areas have benefited from this migration more than the two west coast cities of the San Francisco Bay Area and Seattle, WA. This is no surprise and we see this across the board from those professionals with bachelors degrees through doctorates. However, inspection into Figure 2 suggests other cities (often with much lower cost of living) are benefitting as well.
Beyond the influx to well known hot beds of tech of San Francisco and Seattle, it is interesting to validate the emergence of Salt Lake City, Portland, Denver/Boulder, Albuquerque/Santa Fe/Los Alamos, Austin, Nashville, and Charlotte as emergent tech hubs. Its pretty clear for folks who have lived in Seattle or San Francisco that they are pretty expensive places, especially with respect to housing. Housing in these secondary sized tech hubs is considerably less while quality of life is high and from the looks of it, opportunity, too (recent SF Chronicle on Silicon Valley migration to Austin, TX). Having personally made the move with my family from San Francisco to Boulder, CO, we can safely speak to the high quality of life factor along with “relatively” lower cost of living than the Bay Area. This lovely town of ~100K (and more sunny days than San Diego) also houses satellite offices of the tech titans of: Google, Uber, Twitter, Salesforce, Github, Microsoft, Oracle and a healthy startup and venture capital ecosystem at the base of the Rocky Mountains.
Now, my colleague Zach (Paysa Co-Founder and CTO) and I are both from the great state of Michigan. We did our undergraduate and post-graduate studies there and soon joined the local workforce. We quickly saw the writing on the wall and made our way west for better opportunities, professionally as well as a higher quality of life. From first hand experience of working at “stale” midwestern companies ran by folks who had spent 30–40 years there, novel ideas for growth or alternative ways of doing things (for the better) were not always received well nor were employees compensated well beyond tenure.
One can see from Figure 2 that Michigan is not alone in losing technical talent in the software engineering space to other states largely in the west, south and southwest. The entire midwestern region along with the I-95 corridor on the east coast is simply not attracting professionals in this software engineering vertical relative to other areas of the United States. The one exception along I-95 is New York City. During his tenure as Mayor, Michael Bloomberg made it a top priority to diversify the local economy with an emphasis on “tech”. These bets appear to be paying off as almost every tech titan now has a presence in Manhattan along with an incredibly healthy startup ecosystem.
Now keep in mind, this analysis is limited to professionals in software engineering largely in internet tech. The explosive growth of Northern Virginia is not reflected in this analysis as much of their job gains have been across other parts of the service sector, e.g., consulting, law, non-profit, etc. Boston, being more biotech heavy along with hardware may also not appear high in this analysis as it is not known well represented in the “internet tech” space (surprisingly, Boston’s wages for software engineers are amongst the lowest of cities of similar size/pedigree — more on that in another blog).
Some interesting analyses done by The Atlantic has to do with the tradeoff of housing affordability vs. aggregate upward mobility for millennials. We see from Figure 3 the rough correlation of mobility (averaged across all economic sectors) and affordability to the analysis we present on where the software engineers are moving to.
So if we inspect all these 5.8M engineers in these destinations for technical talent and simply average over their total annual compensation broken out by their maximum attained degree, these professionals (ranging from individual contributors to VPs) are earning substantial wages.
As the economy continues to tip into efficiency gains made by those professionals armed with the tools and wherewithal to enable automation and learning from complex massive data, these professionals are those which laggard communities and cities need to attract to spur economic growth, tax dollars, and prosperity.
The labor market is an “opaque” market. The lack of transparency on the landscape of compensation has yet to be identified beyond hearsay and a directional attempt to understand compensation at three-dimensional level, e.g., company/title/location (Glassdoor and Payscale take this approach). At Paysa, we leverage rigorous techniques in big data and machine learning to reverse engineer the hidden landscape of compensation at the most granular of levels. This enables us to provide personalized market valuations at an individual level using over 10,000+ attributes of who you are. Users can understand the change in their market salary across base, bonus and equity by adding new skills or taking a job at a different company with a different titles. Paysa Jobs allows users to filter jobs by the pay they’d make at these companies as well as the likelihood someone in their position career wise is to obtain this gig (going from software engineer to director of engineering is “ambitious”, statistically speaking in one hop). We know interviewing is a stressful time suck and candidates should be able to divert their time and resources to those jobs in which they will make at or above their desired amount…
