Understanding the salaries for different cities can not only be interesting to know but also beneficial in determining where to live or for reference when looking for your next position in data science. It is also important to note that a higher salary doesn’t necessarily mean more value to you. Ultimately that is up to you, as there are plenty of other factors that determine its value, which I will discuss below. Keep on reading if you would like to know the top 10 cities for annual salary in data science.
Top 10
Most of the top 10 is probably what you would expect. However, there are a few cities that I was surprised not to see ranked as high, along with a few that I was not expecting to see up here. With that being said let's look at the raw list, along with a geo chart I made to visualize this data to gain a better understanding of how cities compare with one another on this list. This data is gathered via ZipRecruiter from job postings as well as third-party data sources [3].
City and its repsective annual salary:
- Santa Clara, California → $147,526
- Mountain View, California → $144,770
- San Francisco, California → $142,723
- Fremont, California → $139,385
- Marysville, Washington → $137,736
- San Jose, California → $134,796
- Oakland, California → $133,398
- Jackson, Wyoming → $132,681
- Alexandria, Virginia → $132,653
- Sunnyvale, California → $131,756
Analysis
Below is a geo chart showing most of the top 10, of which 70% of the list is all in the same region, which is the Bay Area of California in and around San Francisco. The city highlighted below in the darker blue in the middle of the image is Santa Clara, CA, which is the highest salary on this list.
I think it is safe to say that we would expect San Francisco cities are amongst the top and in this list in general. Another city I was expecting is one near Seattle, Washington which leads a lot of the growth in tech. Not only tech, but also places like Boeing, Target, Walmart, and Costo that have offices or are headquartered here, just to name a few.
Jackson, Wyoming
- Perhaps the biggest surprise on this list is Jackson, Wyoming. It took me a while to figure out why a rural area would pay as much. There are some factors like national parks and just natural beauty in general that would persuade top talent. However, I don’t think that is the main reason for this high average. I was surprised to see Amazon here as well — by searching for a real data scientist position and visiting this company’s active listing, which is, of course, similar to why Seattle's pay is so high as well. I would expect that this company is most of the reason for the average being so high.
Alexandria, Virginia
- I was somewhat surprised to see the last city was Alexandria, Virginia. Some companies to point out when looking at some job listings were Booz Allen Hamilton, Deloitte, KPMG, Amazon, and the National Science Foundation, as well as a ton of government positions around Washington D.C.
Perhaps the main reason I was even more surprised by those two cities being on the list, is that these were ahead of New York City, along with other major cities. This reason might just be this specific list as well as having an overall smaller sample size in rural/smaller cities, versus a larger city has a bit of range from low pay to high average pay.
That statement does make me wonder that the Bay Area and Seattle area are very saturated with high salaries and most likely have a low standard deviation.
Here are other reasons to consider a lower or higher salary:
- Cost of living (mortgage/rent/products, etc.)
- If you like the city itself
- If you can work remotely
- Job advancement
Of course, salary is not everything, so what are other factors that non-remote workers would choose these cities?
Here are other reasons to consider for why these particular cities are the best for data science positions, other than the salaries themselves:
- Weather — California, of course, has a lot of sunny days, and Seattle has more temperate conditions so it's not as hot during the summers, as well as less harsh winter conditions than most of the country.
- Natural Beauty — California is on or close to the Pacific Ocean with lots of flora, which can be said about Washington too. Wyoming has a lot of natural beauty too and isn’t as crowded. Alexandria is on the other side of the US, while still being close to the Atlantic Ocean.
- Public Transportation — all cities on this list have good or excellent public transportation, mainly trains, except for Wyoming.
- Hobbies — a lot of cities generally have this last benefit going for it, but it is important to point out that in a combination of the top three, you can enjoy other things like your hobbies more due to the ease and comfortability that the city or location allows. For example, if you hike, run, sail, or follow sports teams, etc., these hobbies can be more accessible.
Summary
To summarize, there are some expected cities in this list, while there are some others that are not. It is also important to note that this is from one list, so it is always best to reference multiple sources as well. The most exciting thing that might happen is the impact of remote jobs on salary since the cost of living does seem so important.
To summarize, here were the top areas of this list:
* San Francisco/Bay Area* Seattle Area* Jackson, Wyoming* Washington D.C. Area
I hope you found my article both interesting and useful. Please feel free to comment down below if you agree or disagree with these particular numbers. Why or why not? What other cities do you think should be on this list? These can certainly be clarified even further, but I hope I was able to shed some light on data science salaries in the top cities.