In 2024, people working in IT management in the United States, earned an average annual salary worth around 168 thousand U.S. dollars. Software developers and project managers all reported being paid on average over 120 thousand U.S. dollars. Despite nearly all categories saw a year-on-year increase in annual compensation, IT support and help desk technicians saw a decrease compared to the previous year
As of 2023, the median wage for employees in healthcare support occupations was about 36,140 U.S. dollars. The occupational group with the highest annual median wage was management occupations. Mean wages for the same occupational groups can be accessed here.
In 2023, the average wage and salary per full-time equivalent employee in the mining industry in the United States was at 126,707 U.S. dollars. The highest wage and salary per FTE was found in the information industry, at 164,400 U.S. dollars.
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Graph and download economic data for Median Personal Income in the United States (MEPAINUSA646N) from 1974 to 2023 about personal income, personal, median, income, and USA.
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Key information about United States Monthly Earnings
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Wages in the United States increased 4.46 percent in January of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: 16 years and over (LES1252881500Q) from Q1 1979 to Q4 2024 about second quartile, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.
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Graph and download economic data for Laborers' Average Hourly Rate of Wages, Weighted for United States (A08139USA052NNBR) from 1860 to 1891 about hours, wages, labor, rate, and USA.
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Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Men (LEU0252881900Q) from Q1 1979 to Q4 2024 about full-time, males, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.
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Graph and download economic data for Average Hourly Earnings of All Employees, Manufacturing (CES3000000003) from Mar 2006 to Feb 2025 about earnings, establishment survey, hours, wages, manufacturing, employment, and USA.
In 2024, professionals from the IT industry earned the highest wages in California, Silicon Valley, with an average of nearly 131 thousand U.S. dollars. Other leading states in terms of highest average salary included Baltimore/Washington D.C., Los Angeles, and New York. Overall, tech salaries in Silicon Valley saw a seven percentage point decrease in average compensation compared to the previous year, while the Baltimore/Washington D.C. area saw a growth in average compensation by nearly six percentage points compared to 2023.
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Wages in Manufacturing in the United States increased to 28.64 USD/Hour in February from 28.54 USD/Hour in January of 2025. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Graph and download economic data for Average Hourly Earnings of All Employees, Total Private (CES0500000003) from Mar 2006 to Feb 2025 about earnings, average, establishment survey, hours, wages, private, employment, and USA.
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Graph and download economic data for Income Before Taxes: Wages and Salaries by Age: from Age 25 to 34 (CXU900000LB0403M) from 1984 to 2023 about age, 25 years +, salaries, tax, wages, income, and USA.
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Dataset Card for Data Science Job Salaries
Dataset Summary
Content
Column Description
work_year The year the salary was paid.
experience_level The experience level in the job during the year with the following possible values: EN Entry-level / Junior MI Mid-level / Intermediate SE Senior-level / Expert EX Executive-level / Director
employment_type The type of employement for the role: PT Part-time FT Full-time CT Contract FL Freelance… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/data-science-job-salaries.
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License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Rochester. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2023
Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Rochester, the median income for all workers aged 15 years and older, regardless of work hours, was $32,132 for males and $28,571 for females.
Based on these incomes, we observe a gender gap percentage of approximately 11%, indicating a significant disparity between the median incomes of males and females in Rochester. Women, regardless of work hours, still earn 89 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.
- Full-time workers, aged 15 years and older: In Rochester, among full-time, year-round workers aged 15 years and older, males earned a median income of $52,701, while females earned $47,224, resulting in a 10% gender pay gap among full-time workers. This illustrates that women earn 90 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Rochester.Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Rochester, showcasing a consistent income pattern irrespective of employment status.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Rochester median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Riverside. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2023
Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Riverside, the median income for all workers aged 15 years and older, regardless of work hours, was $42,921 for males and $30,743 for females.
These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Riverside. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Riverside.
- Full-time workers, aged 15 years and older: In Riverside, among full-time, year-round workers aged 15 years and older, males earned a median income of $57,855, while females earned $50,953, resulting in a 12% gender pay gap among full-time workers. This illustrates that women earn 88 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Riverside.Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Riverside.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Riverside median household income by race. You can refer the same here
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Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: White: Men (LEU0252884000A) from 2000 to 2024 about full-time, males, salaries, workers, earnings, white, 16 years +, wages, median, real, employment, and USA.
In 2023, recent male university graduates in the United States expected to have an average salary of 70,625 U.S. dollars at their first job after graduation while female university graduates expected an average salary of 64,926. In comparison, the expected average starting salary was 66,467 U.S. dollars for all recent college graduates in that year.
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Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over: Black or African American (LEU0252884600Q) from Q1 2000 to Q4 2024 about full-time, African-American, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.
In 2024, people working in IT management in the United States, earned an average annual salary worth around 168 thousand U.S. dollars. Software developers and project managers all reported being paid on average over 120 thousand U.S. dollars. Despite nearly all categories saw a year-on-year increase in annual compensation, IT support and help desk technicians saw a decrease compared to the previous year