Between 2022 and 2032, the fastest growing jobs in the United States have been predicted to be ************************ and *******************. The growth rate was predicted by the U.S. Bureau of Labor Statistics as the highest projected percent change of employment. The United States was recently second in the list of leading countries by renewable energy consumption, so the demand for wind turbine technicians is perhaps understandably high.

According to the Bureau of Labor Statistics, four of the ten fastest growing occupations projected between 2023 and 2033 were in the healthcare sector. Nurse practitioners were projected to be the fastest growing occupation out of these four healthcare-related occupations. From 2023 to 2033, it was expected that employment of nurse practitioners will increase by **** percent. This ranks nurse practitioners ***** overall, after wind turbine service technicians and solar photovoltaic installers. The growth rate of NP has slowed down slightly since projections three years ago.

Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to Jun 2025 about headline figure, establishment survey, manufacturing, employment, and USA.

Job Creation Rates DOL, Bureau of Labor Statistics Nov 2013- Nov 2014

Graph and download economic data for Job Openings: Total Nonfarm (JTSJOL) from Dec 2000 to May 2025 about job openings, vacancy, nonfarm, and USA.

Context:

The Occupational Employment Statistics (OES) and National Compensation Survey (NCS) programs have produced estimates by borrowing from the strength and breadth of each survey to provide more details on occupational wages than either program provides individually. Modeled wage estimates provide annual estimates of average hourly wages for occupations by selected job characteristics and within geographical location. The job characteristics include bargaining status (union and nonunion), part- and full-time work status, incentive- and time-based pay, and work levels by occupation.

Direct estimates are based on survey responses only from the particular geographic area to which the estimate refers. In contrast, modeled wage estimates use survey responses from larger areas to fill in information for smaller areas where the sample size is not sufficient to produce direct estimates. Modeled wage estimates require the assumption that the patterns to responses in the larger area hold in the smaller area.

The sample size for the NCS is not large enough to produce direct estimates by area, occupation, and job characteristic for all of the areas for which the OES publishes estimates by area and occupation. The NCS sample consists of 6 private industry panels with approximately 3,300 establishments sampled per panel, and 1,600 sampled state and local government units. The OES full six-panel sample consists of nearly 1.2 million establishments.

The sample establishments are classified in industry categories based on the North American Industry Classification System (NAICS). Within an establishment, specific job categories are selected to represent broader occupational definitions. Jobs are classified according to the Standard Occupational Classification (SOC) system.

Content:

Summary: Average hourly wage estimates for civilian workers in occupations by job characteristic and work levels. These data are available at the national, state, metropolitan, and nonmetropolitan area levels.

Frequency of Observations: Data are available on an annual basis, typically in May.

Data Characteristics: All hourly wages are published to the nearest cent.

Acknowledgements:

This dataset was taken directly from the Bureau of Labor Statistics and converted to CSV format.

Inspiration:

This dataset contains the estimated wages of civilian workers in the United States. Wage changes in certain industries may be indicators for growth or decline. Which industries have had the greatest increases in wages? Combine this dataset with the Bureau of Labor Statistics Consumer Price Index dataset and find out what kinds of jobs you would need to afford your snacks and instant coffee!

Graph and download economic data for Employment Level (CE16OV) from Jan 1948 to Jun 2025 about civilian, 16 years +, household survey, employment, and USA.

Employment Rate in the United States remained unchanged at 59.70 percent in June. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment Rate in the United States decreased to 4.10 percent in June from 4.20 percent in May of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In October 2024, the civilian labor force amounted to 168.48 million people in the United States. The term civilian labor force is used by the U.S. Bureau of Labor Statistics (BLS) to describe the subset of Americans who have jobs or are seeking a job, are at least 16 years old, are not serving in the military, and are not institutionalized.

Graph and download economic data for All Employees, Government (USGOVT) from Jan 1939 to Jun 2025 about establishment survey, government, employment, and USA.

BackgroundThe fast-changing labor market highlights the need for an in-depth understanding of occupational mobility impacted by technological change. However, we lack a multidimensional classification scheme that considers similarities of occupations comprehensively, which prevents us from predicting employment trends and mobility across occupations. This study fills the gap by examining employment trends based on similarities between occupations.MethodWe first demonstrated a new method that clusters 756 occupation titles based on knowledge, skills, abilities, education, experience, training, activities, values, and interests. We used the Principal Component Analysis to categorize occupations in the Standard Occupational Classification, which is grouped into a four-level hierarchy. Then, we paired the occupation clusters with the occupational employment projections provided by the U.S. Bureau of Labor Statistics. We analyzed how employment would change and what factors affect the employment changes within occupation groups. Particularly, we specified factors related to technological changes.ResultsThe results reveal that technological change accounts for significant job losses in some clusters. This poses occupational mobility challenges for workers in these jobs at present. Job losses for nearly 60% of current employment will occur in low-skill, low-wage occupational groups. Meanwhile, many mid-skilled and highly skilled jobs are projected to grow in the next ten years.ConclusionOur results demonstrate the utility of our occupational classification scheme. Furthermore, it suggests a critical need for skills upgrading and workforce development for workers in declining jobs. Special attention should be paid to vulnerable workers, such as older individuals and minorities.

In February 2025, the unemployment rate for those aged 16 and over in the United States came to 4.5 percent. Service occupations had an unemployment rate of 6.3 percent in that month. The underemployment rate of the country can be accessed here and the monthly unemployment rate here. Unemployment by occupation in the U.S. The United States Bureau of Labor Statistics publish data on the unemployment situation within certain occupations in the United States on a monthly basis. According to latest data released from May 2023, transportation and material moving occupations experienced the highest level of unemployment that month, with a rate of around 5.6 percent. Second ranked was farming, fishing, and forestry occupations with a rate of 4.9 percent. Total (not seasonally adjusted) unemployment was reported at 3.6 percent in March 2023. Other data on the U.S. unemployment rate by industry and class of worker shows comparable results. It should be noted that the data were not seasonally adjusted to account for normal seasonal fluctuations in unemployment. The monthly unemployment by occupation data can be compared to the seasonally adjusted monthly unemployment rate. In March 2023, the seasonally adjusted unemployment rate was 3.5 percent, which was an increase from the previous month. The annual unemployment rate in 2022 was 3.6 percent, down from a high of 9.6 in 2010. Unemployment in the United States trended downward after the coronavirus pandemic, and is now experiencing consistently low rates - a sign of economic stability. Individuals who opt to leave the workforce and stop looking for employment are not included among the unemployed. The civilian labor force participation rate in the U.S. rose to 62.2 percent in 2022, down from 67.1 percent in 2000, before the financial crisis.

Job Offers in the United States increased to 7769 Thousand in May from 7395 Thousand in April of 2025. This dataset provides the latest reported value for - United States Job Openings - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Job Quits Rate in the United States increased to 2.10 percent in May from 2 percent in April of 2025. This dataset includes a chart with historical data for the United States Job Quits Rate.

Graph and download economic data for Employment-Population Ratio (EMRATIO) from Jan 1948 to May 2025 about employment-population ratio, civilian, 16 years +, household survey, employment, population, and USA.

The seasonally-adjusted national unemployment rate is measured on a monthly basis in the United States. In February 2025, the national unemployment rate was at 4.1 percent. Seasonal adjustment is a statistical method of removing the seasonal component of a time series that is used when analyzing non-seasonal trends. U.S. monthly unemployment rate According to the Bureau of Labor Statistics - the principle fact-finding agency for the U.S. Federal Government in labor economics and statistics - unemployment decreased dramatically between 2010 and 2019. This trend of decreasing unemployment followed after a high in 2010 resulting from the 2008 financial crisis. However, after a smaller financial crisis due to the COVID-19 pandemic, unemployment reached 8.1 percent in 2020. As the economy recovered, the unemployment rate fell to 5.3 in 2021, and fell even further in 2022. Additional statistics from the BLS paint an interesting picture of unemployment in the United States. In November 2023, the states with the highest (seasonally adjusted) unemployment rate were the Nevada and the District of Columbia. Unemployment was the lowest in Maryland, at 1.8 percent. Workers in the agricultural and related industries suffered the highest unemployment rate of any industry at seven percent in December 2023.

According to recent data of U.S. Bureau of Labor Statistics, 441.7 thousand people were working in the motion picture and sound recording industries in the United States as of January 2024. That value dropped in 2023 to 422 thousand employees before rebounding the following year.

As per Cognitive Market Research's latest published report, the Global Online Recruitment market size was $27.98 Billion in 2021 and it is forecasted to reach $41.83 Billion by 2029. Online Recruitment Industry's Compound Annual Growth Rate will be 7.3% from 2023 to 2030. Factors Impacting on Online Recruitment Market

An increasing number of job openings has created a massive demand for modern recruiting software, to streamline hiring processes which, include resume management, employee evaluation, assessment tools, and others. According to the Bureau of Labor Statistics 2022, the U.S. economy is projected to add 8.3 million jobs from 2021 to 2031 and it is projected to increase from 158.1 million to 166.5 million and grow 0.5 percent annually.

https://www.bls.gov/news.release/pdf/ecopro.pdf

On the other hand, the growing expansion of cloud-based technologies, availability of high-bandwidth internet infrastructure, and rising use of mobile-based recruitment are some of the other major driving factors for the growth of online recruitment market. Increasing focus on automation is estimated to create lucrative opportunities for the online recruitment market and the increasing incidents of online fraud can hinder the growth of the market.

Market Trends:

The adoption of advanced technologies such as big data, cloud computing, AI, and others is positively impacting the global online recruitment market. A major trend driving the global online recruiting industry is the expansion of high-speed internet access and internet-capable devices like tablets, laptops, and smartphones. Due to this, individuals can easily apply for more positions, and companies have access to a wider choice of candidates. Introduction of Online Recruitment.

Online recruitment is also known as E-recruitment, it uses web-based technology for the various processes of attracting, assessing, selecting, recruiting, and onboarding job candidates. Online recruitment is a way to provide businesses with an efficient and cheaper way to fill positions.

In October 2024, about 133.5 million people in the United States were employed on a full-time basis. In line with the definition of the BLS, full-time workers are persons who usually work 35 hours or more per week. Seasonal adjustment is a statistical method for removing the seasonal component of a time series used when analyzing non-seasonal trends, whereas non-seasonally-adjusted reflects the actual current data.