This Dataset indicates average salary by position title and grade for full-time regular employees. Data excludes elected, appointed, non-merit and temporary employees. Underfilled positions are also excluded from the dataset. Update Frequency : Annually

This dataset provides the average earnings by student group per district.  Wage records are obtained from the Massachusetts Department of Unemployment Assistance (DUA) using a secure, anonymized matching process with limitations. For details on the process and suppression rules, please visit the Employment and Earnings of High School Graduates dashboard.

This dataset is one of three containing the same data that is also published in the Employment and Earnings of High School Graduates dashboard: Average Earnings by Student Group Average Earnings by Industry College and Career Outcomes

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.

In 2022, the average annual income of a college graduate with a Bachelor's degree in the United States was 52,000 U.S. dollars. This is a decrease from the previous year, when the median income for college grads was around 56,156 U.S. dollars.

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.

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.

The wages on the Job Bank website are specific to an occupation and provide information on the earnings of workers at the regional level. Wages for most occupations are also provided at the national and provincial level. In Canada, all jobs are associated with one specific occupational grouping which is determined by the National Occupational Classification. For most occupations, a minimum, median and maximum wage estimates are displayed. They are update annually. If you have comments or questions regarding the wage information, please contact the Labour Market Information Division at: NC-LMI-IMT-GD@hrsdc-rhdcc.gc.ca

This dataset provides annual personal income estimates for State of Iowa produced by the U.S. Bureau of Economic Analysis beginning in 1997. Data includes the following estimates: personal income, per capita personal income, wages and salaries, supplements to wages and salaries, private nonfarm earnings, compensation of employees, average compensation per job, and private nonfarm compensation.

Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income for Iowa is the income received by, or on behalf of all persons residing in Iowa, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s annual midyear (July 1) population estimates.

Wages and salaries is defined as the remuneration receivable by employees (including corporate officers) from employers for the provision of labor services. It includes commissions, tips, and bonuses; employee gains from exercising stock options; and pay-in-kind. Judicial fees paid to jurors and witnesses are classified as wages and salaries. Wages and salaries are measured before deductions, such as social security contributions, union dues, and voluntary employee contributions to defined contribution pension plans.

Supplements to wages and salaries consists of employer contributions for government social insurance and employer contributions for employee pension and insurance funds.

Private nonfarm earnings is the sum of wages and salaries, supplements to wages and salaries, and nonfarm proprietors' income, excluding farm and government.

Compensation to employees is the total remuneration, both monetary and in kind, payable by employers to employees in return for their work during the period. It consists of wages and salaries and of supplements to wages and salaries. Compensation is presented on an accrual basis - that is, it reflects compensation liabilities incurred by the employer in a given period regardless of when the compensation is actually received by the employee.

Average compensation per job is compensation of employees divided by total full-time and part-time wage and salary employment.

Private nonfarm compensation is the sum of wages and salaries and supplements to wages and salaries, excluding farm and government.

More terms and definitions are available on https://apps.bea.gov/regional/definitions/.

This dataset presents the annual changes since 2013 in the cyclical retirement age, as well as various end-of-career indicators (average durations spent in and out of employment between the age of 50 and retirement), according to the level of disability Disabilities are identified by the fact that people declare themselves limited, strongly or not, in the activities that people usually do (the so-called “GALI” indicator according to its English acronym: Global activity limitation indicator). Persons with disabilities are identified as those who claim to be severely limited. The data update the results of the publication “People with disabilities leave the labour market younger but liquidate their retirement later” (Studies and results n° 1143) In the case of a sample survey, some indicators can be noisy and it is better to look at them on average over several years. Source: INSEE, Employment/Salary Survey: DREES

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.

This table contains information about jobs and wages of employees working at enterprises in the Netherlands, broken down by locus of control of these enterprises. A distinction is made between domestically and foreign controlled enterprises. The figures refer only to enterprises with employees. For these enterprises, the total number of jobs is given as well as the composition of these jobs by employee characteristics (job status, gender, age, country of origin, and wage levels). The average taxable annual salary per job is also given.

Data available 2008-2011.

Status of the figures: The figures in this table are definite.

Changes as of January 10th 2018: None, this table was stopped.

When will new figures be published? This table is stopped.

Salary information for State of Oklahoma employees by pay band, including average, maximum and minimum, and the size of the range by pay band.

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)

Analysis of ‘Average wages of the main job by period, type of working day, nationality and decile. EPA (API identifier: 13929)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-348-13929 on 08 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Average wages of the main job by period, type of working day, nationality and decile. Annual. Economically Active Population Survey

--- Original source retains full ownership of the source dataset ---

Employment income (in 2019 and 2020) by detailed major field of study and highest certificate, diploma or degree, including work activity (full time full year, part time full year, or part year).

The U.S. Bureau of Economic Analysis’ Total Full-Time and Part-Time Employment data provides one of the most comprehensive, publicly available accountings of average annual employment. Beyond full- and part-time employment types, it includes farm employment and other sectors that aren’t always included in other sources, such as Public Administration (with more detail of federal than state and local employment in this category). It also includes and distinguishes both Wage and Salary employees from Proprietors who own their own unincorporated businesses and handle taxation chiefly as personal income. Proprietors tend to be single-person or small businesses and can include construction or repair workers, babysitters, ride-share drivers, artists, local grocers, housekeepers, various freelancers and consultants, and some attorneys and doctors.

The NBA and WNBA are the two top leagues for basketball in the United States for men and women, respectively. In the NBA, players took home an average annual salary of over 12 million U.S. dollars for the 2023/24 season, with the league's minimum salary set at 1.16 million U.S. dollars that year. In comparison, players in the WNBA received an average annual pay of 119.59 thousand U.S. dollars, with the highest-earning players in the WNBA receiving around 252 thousand U.S. dollars annually.

Average earnings, by age group and highest level of education, from the 2016 Census of Population.

Wages in China increased to 120698 CNY/Year in 2023 from 114029 CNY/Year in 2022. This dataset provides - China Average Yearly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Average hourly and weekly wage rate, and median hourly and weekly wage rate by National Occupational Classification (NOC), type of work, gender, and age group.