Employees in Greece spend an average of 13 years with their employers as of 2023, the longest average job tenure among European countries. Among the provided countries, Denmark had the shortest average job tenure, at 7.5 years. In most European countries, men spend more time with a single employer on average than women. Notable exceptions to this trend come from a number of post-communist countries in central and eastern Europe - Romania, Bulgaria, Lithuania, Latvia, and Estonia-.

As of January 2024, the median number of years (tenure) that wage and salary workers in the manufacturing industry had been with their current employer was *** years in the United States. Workers in the education and health services industry had a median of *** years with their current employer. Employee tenure is a measure of how long wage and salary workers have been with their current employer. Data on employee tenure can be used as a gauge of employment security, where an increase in tenure means improving security, and a decrease in tenure shows deteriorating security.

Number of employed persons by job tenure, North American Industry Classification System (NAICS) and gender.

Number of employed persons by job tenure, National Occupational Classification (NOC) and sex, last 5 years.

In 2023, the average tenure of contract and temporary employees in the United States was **** weeks. Tenure is defined as the duration of employment with the staffing firm.

As of January 2024, the median number of years (tenure) that wage and salary workers had been with their current employer was *** years in the United States. This is a decrease from 2022, when the median tenure was also *** years. Employee tenure is a measure of how long wage and salary workers have been with their current employer. Data on employee tenure can be used as a gauge of employment security, where an increase in tenure means improving security, and a decrease in tenure shows deteriorating security.

This statistic shows the average job tenure of employees in a Canada in 2022, distinguished by major occupations. In 2022, the average job tenure for Canadian employees in management occupations stood at ***** months.

Number of employed persons by job tenure, type of work (full- and part-time employment), gender, and age group, annual.

This statistic shows the average job tenure of employees in a Canada in 2022, distinguished by major industry. In 2022, the average job tenure for Canadian employees in agriculture stood at ***** months.

The Synthetic Employee Attrition Dataset is a simulated dataset designed for the analysis and prediction of employee attrition. It contains detailed information about various aspects of an employee's profile, including demographics, job-related features, and personal circumstances.

The dataset comprises 74,498 samples, split into training and testing sets to facilitate model development and evaluation. Each record includes a unique Employee ID and features that influence employee attrition. The goal is to understand the factors contributing to attrition and develop predictive models to identify at-risk employees.

This dataset is ideal for HR analytics, machine learning model development, and demonstrating advanced data analysis techniques. It provides a comprehensive and realistic view of the factors affecting employee retention, making it a valuable resource for researchers and practitioners in the field of human resources and organizational development.

FEATURES:

Employee ID: A unique identifier assigned to each employee. Age: The age of the employee, ranging from 18 to 60 years. Gender: The gender of the employee Years at Company: The number of years the employee has been working at the company. Monthly Income: The monthly salary of the employee, in dollars. Job Role: The department or role the employee works in, encoded into categories such as Finance, Healthcare, Technology, Education, and Media. Work-Life Balance: The employee's perceived balance between work and personal life, (Poor, Below Average, Good, Excellent) Job Satisfaction: The employee's satisfaction with their job: (Very Low, Low, Medium, High) Performance Rating: The employee's performance rating: (Low, Below Average, Average, High) Number of Promotions: The total number of promotions the employee has received. Distance from Home: The distance between the employee's home and workplace, in miles. Education Level: The highest education level attained by the employee: (High School, Associate Degree, Bachelor’s Degree, Master’s Degree, PhD) Marital Status: The marital status of the employee: (Divorced, Married, Single) Job Level: The job level of the employee: (Entry, Mid, Senior) Company Size: The size of the company the employee works for: (Small,Medium,Large) Company Tenure: The total number of years the employee has been working in the industry. Remote Work: Whether the employee works remotely: (Yes or No) Leadership Opportunities: Whether the employee has leadership opportunities: (Yes or No) Innovation Opportunities: Whether the employee has opportunities for innovation: (Yes or No) Company Reputation: The employee's perception of the company's reputation: (Very Poor, Poor,Good, Excellent) Employee Recognition: The level of recognition the employee receives:(Very Low, Low, Medium, High)

Attrition: Whether the employee has left the company, encoded as 0 (stayed) and 1 (Left).

As of January 2024, the median number of years (tenure) that high school graduate wage and salary workers in the United States had been with their current employer was *** years. The workers with a doctoral or professional degree had a median tenure of *** years with their current employer. Employee tenure is a measure of how long wage and salary workers have been with their current employer. Data on employee tenure can be used as a gauge of employment security, where an increase in tenure means improving security, and a decrease in tenure shows deteriorating security.

The "Quality of employment" framework developed under the lead of UNECE (United Nations Economic Commission for Europe) represents a neutral and comprehensive approach to assess quality of employment in its multiple facets. It defines 68 indicators on seven dimensions that address employment quality from the perspective of the employed person. Its design also facilitates international comparison. For statistical institutes, researchers and policy users looking to build and analyse datasets using these indicators, the framework explained in a handbook published by UNECE. Using the UNECE framework, Eurostat has compiled data on employment quality for the EU countries that is provided in the Eurostat database.

LFS in one of the sources which provides data for filling some of the indicators. The section 'Quality of employment' reports annual results from the EU-LFS concerning some of those indicators.

In particular:

• Long working hours in main job: percentage of employed persons usually working 49 hours or more per week;
• Weekly working hours: Average number of usual weekly working hours of employed persons;
• Work on weekends: Percentage of employed persons usually working at Saturday or Sunday;
• Job tenure Percentage of employed persons by duration of employment with current employer by number of years;
• Temporary employment agency workers: Percentage of employed persons working for a temporary work agency;
• Precarious employment: Percentage of employees with a short-term contract of up to 3 months.

More information on Eurostat indicators about Quality of employment is available on the dedicated webpage.

General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

• administrative data • age dependency ratio • age groups • age structure • agriculture • armed force • average salary • average tenure s • average wages • births • broad economic activities • civil employment • civilian labour • collective dismissals • constant prices • current prices • death rates • dependent employment • discouraged workers • dismissals • duration of unemployment • earning-dispersion measures • earnings • employee density • employee turnover • employee union • employees • employment • employment protection legislation • employment ratio • employment status • exchange rate • finance • full-time • full-year equivalent employee • gender • gross earnings • health • incidents • independent workers • industry • Involuntary part time workers • job tenure • jobs • labour • labour force • labour force forecasts • labour market • labour market fluidity • labour market programmes • labour regulation • low pay incidence • median wages • membership • migration rates • minimum wages • national legislation • natural increase rates • pension age • population • population baseline • population estimates females • population projections • PPP • professional status • real estate • rigidness • salary earner ratio • salary earners • self-employed • services • short-time workers • standardised age groups • statistics • strict regulation • strictness of legislation • survey data • synthetic indicators • total employment • total increase rates • trade union • trade union members • transport • turnover rate • unemployment • union members • unpaid family workers • unpaid workers • vital statistics • weekly hours • working age ratio

Average productivity loss and average cost of productivity loss by work type, job tenure, gender and age group–primary analysis of a US manufacturing company.

This set of quarterly cubes provides employee population data. The numbers reflect the actual number of employees at the end of a quarter but, for many agencies, may actually reflect employment at the end of the pay period just prior to the end of the quarter. The scope of this raw data set includes all data elements used in the creation of the FedScope Employment Cube (http://www.fedscope.opm.gov/). The following workforce characteristics are available for analysis: Agency, State/Country, Age (5 year interval), Education Level, Gender, GS & Equivalent Grade, Length of Service (5 year interval), Occupation, Occupation Category, Pay Plan & Grade, Salary Level ($10,000 interval), STEM Occupations, Supervisory Status, Type of Appointment, Work Schedule, Work Status, Employment, Average Salary, and Average Length of Service. The OPM Enterprise Human Resources Integration-Statistical Data Mart (EHRI-SDM) is the source for all FedScope data. Data is processed on a quarterly basis (i.e. March, June, September and December).

This statistic depicts the expected average reskilling needs across companies worldwide between 2018 and 2022, broken down by length per employee. During the survey, respondents expected that ** percent of their employees will require reskilling of less than one month by 2022.

Apprenticeship duration, apprenticeship planned length of stay and length of employmentAcademic year: 2014/15 to 2023/24 full academic yearIndicators: Starts, Starts (used in duration calculations), Average expected durationFilters: Age group, Detailed level, Length of employment, Planned length of stay

This set of quarterly cubes provides employee population data for the new Ethnicity and Race Indicator (ERI). The numbers reflect the actual number of employees as of a specific point in time. The following workforce characteristics are available for analysis: Agency, State/Country, Age (5 year interval), Education Level, Ethnicity and Race Indicator (ERI), Length of Service (5 year interval), GS & Equivalent Grade, Occupation, Occupation Category, Pay Plan & Grade, Salary Level ($10,000 interval), STEM Occupations, Supervisory Status, Type of Appointment, Work Schedule, Work Status, Employment, Average Salary, Average Length of Service. Diversity cubes will be available for the most recent 8 quarters and the 5 previous end of fiscal year (September) files.

This statistic shows the average length of agency work assignments in selected countries worldwide in 2016. In China, 100 percent of agency work assignments lasted for more than three months. In Germany, 66 percent of agency work assignments did.

Annual workforce population statistics on the federal public service from March 2010 to March 2024 which includes the core public administration and separate agencies. The datasets included are: - Population of the federal public service - by department or agency - and by tenure - and by province or territory of work - and by age band - and average age - and by executive level - and by first official language - and by sex - by province or territory of work and tenure - by province or territory of work - in the National Capital Region - by tenure - by first official language - by age band