In 2025, the Midwest area was the U.S. region with the highest annual physician compensation. Physicians earned some 385,000 U.S. dollars on average in this area. Low number of physicians in these states with many rural areas means less competition for doctors, potentially increasing pay.

Located in the north of the country, Lombardy had the highest mean gross salary in 2024, while workers in Basilicata earned the lowest average wages nationwide. The figure for Lombardy amounted to ****** euros, around *** euros more than in Lazio, where the capital Rome is situated, as reported by Job Pricing. Trentino-South Tyrol was the region with the second-highest average gross salary, ****** euros per year. The last positions of the raking were occupied by the southern regions, with an average wage of ****** euros. High wages and large pay gap  According to the same source, employees working in banking and financial services had some of the largest salaries in Italy. However, men earned roughly ** percent more than women (****** euros versus ****** euros). Similarly, the annual gross salary in the insurance industry was ** percent higher in favor of men. Low-wage workers The south of Italy was also the place registering the highest percentage of low paid employees. These are employees with an hourly salary of less than ********** of the median salary over the total number of employees. More specifically, in the south and on the islands, the share of low-wage employees was **** and **** percent, respectively. In the northern regions, the share amounted to only *** percent.

This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html

Data Disclosure Exemptions: Information disclosed in this dataset is subject to FOIA Exemption Act, 5 ILCS 140/7 (Link:https://www.ilga.gov/legislation/ilcs/documents/000501400K7.htm)

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Graph and download economic data for Median Family Income in West Census Region (MEFAINUSWEA646N) from 1953 to 2023 about West Census Region, family, median, income, and USA.

This statistic shows average salaries of IT professionals worldwide in 2017, by region. The average salaries of IT professionals in North America amounted to about **** thousand U.S. dollars in 2017.

VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)

FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations

LAST UPDATED January 2019

DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.

DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html

American Community Survey (2001-2017) http://api.census.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.

Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.

Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.

Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.

In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.

Dataset Summary

Briefly summarize the dataset, its intended use and the supported tasks. Give an overview of how and why the dataset was created. The summary should explicitly mention the languages present in the dataset (possibly in broad terms, e.g. translations between several pairs of European languages), and describe the domain, topic, or genre covered.

  Supported Tasks and Leaderboards

For each of the tasks tagged for this dataset, give a brief description of the tag… See the full description on the dataset page: https://huggingface.co/datasets/Einstellung/demo-salaries.

This dataset presents the average daily wage earnings during the preceding calendar month from regular wage/salaried employment among the regular wage/salaried employees in CWS for each State/ UT. For 2023-24, Chandigarh's entire area has been considered urban for this survey. Before 2019-20, Ladakh was part of Jammu and Kashmir, and since 2020-21, Daman and Diu have been merg ed with Dadra and Nagar Haveli to form the union territory of Dadra and Nagar Haveli and Daman and Diu.

Graph and download economic data for Median Personal Income in Northeast Census Region (MEPAINUSNEA646N) from 1974 to 2023 about Northeast Census Region, personal income, personal, median, income, and USA.

Average full-time hourly wage paid and payroll employment by type of work, economic region and National Occupational Classification (NOC), 2016 and 2017.

Gross weekly earnings of full-time employees by region, UK, quarterly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.

Each year, the City of Boston publishes payroll data for employees. This dataset contains employee names, job details, and earnings information including base salary, overtime, and total compensation for employees of the City.

See the "Payroll Categories" document below for an explanation of what types of earnings are included in each category.

Explore the progression of average salaries for graduates in Economic And Social Development Of Regions from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Economic And Social Development Of Regions relative to other fields. This data is essential for students assessing the return on investment of their education in Economic And Social Development Of Regions, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Urban And Regional Design from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Urban And Regional Design relative to other fields. This data is essential for students assessing the return on investment of their education in Urban And Regional Design, providing a clear picture of financial prospects post-graduation.

Wages In the Euro Area increased 3.40 percent in March of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Euro Area Wage Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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

job_title… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/data-science-job-salaries.