Data Analytics

Tech Jobs and Salaries- An Interactive Map

The U.S. Bureau of Labor Statistics surveys over 1 million establishments for 800 occupations in 580 areas of the United States and have made the data publicly available. The data set includes employment numbers, wages, and other details on the labor market. The results are staggering, the data is extremely large and difficult for readers to digest, until now.

This interactive map shows the best locations for tech jobs in the U.S. according to employment numbers from the U.S. BLS’s latest Occupational Employment and Wage Statistics survey for Computer and Mathematical occupations in May 2021. It includes statistics for where tech jobs pay the best, where tech jobs have the highest hourly pay or salary, and where tech jobs have the highest density of employment.

Visualizing tech hubs in the U.S can be very useful for IT professionals, software developers, remote workers, and technical recruiters to find talent and opportunity in their area.

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Field Descriptions

Name of Metropolitan Statistical Area and primary state(s).

ID – Unique identification number of Metropolitan Statistical Area

Total Employment – Estimated total employment of Computer and Mathematical Occupations, rounded to the nearest 10 and excluding self-employed.

Jobs per 1000 – The number of Computer and Mathematical jobs per 1,000 jobs in the given area.

Location Quotient – the ratio of an occupation’s share of employment in a given area to that occupation’s share of employment in the U.S. as a whole. For example, an occupation that makes up 10 percent of employment in a specific metropolitan area compared with 2 percent of U.S. employment would have a location quotient of 5 for the area in question.

Hourly mean – Mean hourly wage in dollars.

Hourly range – Hourly 10th percentile wage to hourly 90th percentile wage in dollars.

Hourly median – Hourly median wage (or the 50th percentile) in dollars.

Annual mean – Mean annual wage in dollars.

Annual range – Annual 10th percentile wage to annual 90th percentile wage in dollars.

Annual median – Annual median wage (or the 50th percentile) in dollars.


#  = indicates a wage equal to or greater than $100.00 per hour or $208,000 per year

*  = indicates that a wage estimate is not available

**  = indicates that an employment estimate is not available

This map uses the data for Computer and Mathematical Occupations as defined by the U.S. BLS. This OEWS dataset includes the following occupations:

  • Computer Systems Analysts
  • Information Security Analysts
  • Computer and Information Research Scientists
  • Computer Network Support Specalists
  • Computer User Support Specialists
  • Computer Network Architects
  • Network and Computer Systems Administrators
  • Database Administrators and Architects
  • Computer Programmers
  • Software Developers and Software Quality Assurance Analysts and Testers
  • Web Developers and Digital Interface Designers
  • Other Computer Occupations
  • Actuaries
  • Mathematicians
  • Operations Research Analysts
  • Statistians
  • Data Scientists and other Mathematical Occupations

The Science behind the Data

The U.S BLS releases the The Occupational Employment and Wage Statistics survey on a semi-annual basis using unemployment insurance files from metropolitan statistical areas (MSAs) defined by the Office of Management and Budget. These MSAs span across multiple states and territories, but thankfully the U.S. Census Bureau provides the coordinates of the metropolitan and metropolitan boundaries as of 2018 which can then be mapped into a GIS application.

The OEWS data is formatted and converted to an array with Python and merged into an the Census coordinates according to its MSA ID string. The resulting dataset is then loaded and displayed into a Leaflet JavaScript map.

Grey areas on the map are rural areas and territories where no data is collected. Light yellow areas without data listed are micropolitan areas with populations between 10,000 and 50,000. Data on these areas may be collected and available through other sources.


As previously stated, this dataset is very large and can be difficult to navigate without a technical background. The data is unavailable through the BLS API, only raw CSV files are provided and it is split by MSA and non-metropolitan areas.

Additionally, the unique identifiers for the data requires extensive wrangling. For reasons unknown, area IDs can have preceding 0s or use alternate coding between CBSFP and NACTA

Since this includes studies that were done in May 2020, it also captures the most conservative numbers of employment, when many employers were closed. Notes on release.


The result is an interactive map that enables you to visualize where the tech hubs are within the US with fine detail and view all available statistics on that area. It allows the user to zoom into specific cities to see employment numbers, location quotients, hourly, and annual wages for that area. Since all of this data is reported by the U.S. Bureau of Labor Statistics, all of the data is empirical and based on existing jobs, not job listings.

This map can be extremely useful for IT professionals, remote workers, and recruiters that are looking for job insights. Despite popular belief, you do not have to move to Silicon Valley to find a tech job, tech opportunities and talent can be found throughout all of the U.S.

This data is also available directly from the BLS’s website with non-metropolitan areas, but the maps are not interactive and do not display detailed stats. Other online maps also use data from job postings, not employment, and leave out many critical areas and statistics.


The data is available, but sometimes it can be overwhelming. With data analysis you can expose areas of opportunity and make a decision based on that analysis. As a cloud engineer seeking employment through the US, this tools helps me explore the opportunities available and decide where my efforts are best spent.

Throughout this website you can find data, tools, tutorials, and articles on cloud technology, security, technology, business, and other insights that may also aid your search.