In January 2025, President Trump ordered a pause on funding for the U.S. Agency for International Development (USAID) and a 90-day review of all U.S. foreign assistance. By the end of March, the review had been completed, 83 percent of USAID programs were terminated, and it was announced that certain USAID functions would be overtaken by the Department of State while all others would be discontinued. Staff for USAID was reduced from around 10,000 to just 15 statutorily required positions. As of April 15, 2025, around 19 thousand jobs had been lost from USAID and their implementing partners who have had to lay off or furlough employees due to the funding freeze.

Dataset

This dataset was created by Toby Jolly

Released under Other (specified in description)

Contents

According to Ipsos Consolidated Economic Indicators based on monthly surveys conducted by Ipsos, the sub-index for the job situation in Israel stood at **** points in April 2020, down from **** points in the previous month. In comparison, the global average sub-index for the job situation stood at **** points in April 2020.

This dataset provides a detailed overview of IT job vacancies in the Asia-Pacific region, encompassing countries such as Australia, Indonesia, Malaysia, the Philippines, Singapore, and Hong Kong. It includes information on job titles, required tools and technologies, programming languages, certifications, job levels, and locations.

itjob_header.csv: - jobid: Unique identifier for each job listing - country: Country where the job is located - level: Job level (e.g., Junior, Middle, Senior) - specialisation: Area of specialisation - salary_from: Minimum salary offered - salary_to: Maximum salary offered - currency: Currency of the salary - type: Type of employment (e.g., Full-time, Part-time) - mode: Work mode (e.g., Hybrid, Remote, Office) - visa_sponsorship: Indicates if visa sponsorship is available - work_experience_years: Required years of experience - education_level: Required education level

itjob_main.csv: - jobid: Unique identifier for each job listing - title: Job title - source_classification: Classification of the job role

itjob_tools.csv: - tool_id: Unique identifier for each tool - jobid: Unique identifier for each job listing - tool_text: Name of the tool or technology required

itjob_prog_lang.csv: - prog_lang_id: Unique identifier for each programming language - jobid: Unique identifier for each job listing - prog_lang_text: Name of the programming language required

itjob_certification.csv: - cert_id: Unique identifier for each certification - jobid: Unique identifier for each job listing - certification_text: Name of the certification required - is_mandatory: Indicates if the certification is mandatory (1) or not (0)

itjob_main_spec.csv: - addit_spec_id: Unique identifier for each additional specialisation - jobid: Unique identifier for each job listing - addit_spec_text: Description of the additional specialisation

List of Jobs Posts across several job application sites.

Vietnam Jobs Dataset

Overview

The jobs.csv dataset contains 85k job postings from various cities and industries in Vietnam, providing insights into the job market as of April 22, 2025. The data includes details about job titles, locations, salaries, experience requirements, and job fields, making it a valuable resource for analyzing salary trends, regional job distribution, and industry demands.

Dataset Description

• File Name: jobs.csv
• Format: Comma-Separated Values (CSV)
• Size: 215 rows (excluding header)
• Source: Internal data collection (specific source not provided)
• Date: Reflects job market data as of April 22, 2025

Data Schema

The dataset includes the following columns:

Notes on Data

• Salary Values: Salaries are provided in VND (Vietnamese Dong) or USD. For consistency, convert USD to VND using an exchange rate (e.g., 1 USD = 25,000 VND).
• Experience: The experience field uses Vietnamese phrases like "không yêu cầu" (no experience required), "trên 1 năm" (over 1 year), or ranges like "2 - 5 năm". Parsing into numerical years is recommended for analysis.
• City Names: City names may vary in format (e.g., "Hồ Chí Minh", "HCM", "hà nội"). Standardize to "Ho Chi Minh City" and "Hanoi" for consistency.
• Job Fields: The job_fields column contains comma-separated values, allowing a single job to belong to multiple industries (e.g., "Sales, Marketing").
• Missing Data: Some fields, particularly salary_min and salary_max, may be missing or zero. Filter out invalid entries for accurate analysis.

Usage

This dataset can be used for:

• Market Analysis: Identify high-paying industries (e.g., banking, management) and salary trends by experience or position level.
• Regional Insights: Analyze job distribution across cities, with a focus on urban centers like Ho Chi Minh City and Hanoi.
• Career Planning: Understand entry-level opportunities, particularly in customer service and telesales, which offer competitive salaries for candidates with no experience.
• Policy and Research: Study labor market dynamics, such as the demand for English-speaking talent or regional salary disparities.

Example Questions

• Which cities have the highest number of job postings and average salaries?
• What are the top-paying job fields, and how do they compare to entry-level roles?
• How does experience impact salaries across different industries?
• Are there niche roles (e.g., technical or medical) with unusually high salaries?

Data Cleaning Recommendations

To prepare the dataset for analysis, consider the following steps:

1. Standardize City Names: Convert variations like "HCM" or "hà nội" to "Ho Chi Minh City" and "Hanoi".
2. Convert Salaries: Multiply USD salaries by 25,000 to convert to VND for consistency.
3. Parse Experience: Convert text-based experience (e.g., "2 - 5 năm") to numerical values (e.g., 3.5 years). Treat "không yêu cầu" as 0 years.
4. Handle Missing Salaries: Filter out rows where both salary_min and salary_max are zero or missing, or impute using industry avera...

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for electrical engineering (april 2004) in the U.S.

Dataset

This dataset was created by Suhail Haque Rafi

Contents

Job Growth Statistics: Statistics on job growth are essential in understanding the state and trajectory of an economy because they offer insight into the shifting dynamics of labor markets. By measuring net job addition or subtraction over a certain timeframe, employment growth statistics allow policymakers, companies, and individuals to make well-informed decisions regarding workforce planning, investment decisions, or career choices. Statistics on job growth provide a key measure of economic development as they show whether an economy is expanding, contracting, or remaining stable. Positive employment growth numbers often signal healthy economies with increased consumer spending and company confidence. Conversely, negative or stagnant job growth indicates a slowdown or recession. Furthermore, statistics on employment growth may also be used to highlight developing markets and professions for policymakers as well as job seekers in finding prospective development areas. As such, employment data provides an essential means of measuring an economy's current state and future direction, as well as helping shape policies and initiatives within it. Editor’s Choice From 2020-2030; job growth in the US is anticipated to be 5.3%. Nurse practitioners are predicted to experience the highest job growth; between 2021-2031 at 45.7%; 2019 alone saw sectors producing goods create 188,000 new jobs. Leisure and hospitality job creation decreased by 47% year-on-year between April 2020 and March 2021. President Clinton created 19 million new employment opportunities between June and July of 2022 and 528,000 nonfarm payroll employees were gained; yet by April 2020 20.5 million jobs had been lost from the economy as a whole. By 2031, it is projected that employment opportunities across the nation will reach 166.5 million; over that same timeframe childcare service workers have seen their ranks decline by 336,000. Since the COVID-19 outbreak, healthcare employment levels have suffered a dramatic decrease. By some accounts, over one and a half million employees may have left healthcare jobs since 2016. (Source: zippia.com)

This round of Eurobarometer surveys queried respondents on a few standard Eurobarometer measures such as whether they attempted to persuade others close to them to share their views on subjects they held strong opinions about, whether they discussed political matters, and how they viewed the need for societal change, but the primary focus of the surveys was on employment, unemployment, and gender equality. During the fieldwork for Eurobarometer 44.3 (see EUROBAROMETER 44.3: HEALTH CARE ISSUES AND PUBLIC SECURITY, FEBRUARY-APRIL 1996 [ICPSR 6752]), an oversample (approximately 300 per country) of unemployed persons and housewives/househusbands, aged 15 years and over, was added to the basic sample and subsequently administered an additional set of questions. Students and retired were excluded from the oversample. Respondents who were employed or self-employed were asked questions concerning their job titles, the ratio of women to men holding the same title, number of people employed at their workplaces, how long they were continuously employed/self-employed, how they found out about their jobs, the type of organizations for which they worked, the number of hours worked, job satisfaction, the type of communication equipment used, and the circumstances under which they would reduce their hours or take unpaid leave. Employed and self-employed respondents were asked about the pay, training, skill level, variety, amount, pressure, and interest involved in their work. They also compared their jobs with jobs they were doing five years ago. Non-self-employed workers provided additional information regarding their level of involvement in decisions that affected their jobs, existence of promotional opportunities, indices of pay raises or dismissal, likelihood of leaving their jobs, and commitment to their current employers. Questions posed to unemployed respondents covered how long they had been unemployed, their former occupation, reasons for leaving their last position, and whether they had received any compensation. They were also asked if they were looking for a job, what approaches they used to find a job, the amount of time spent looking for a job, problems in trying to find a job, whether they would consider a position requiring different skills, a lower level of skills, worse physical conditions, or different hours, or if they would relocate. These respondents also indicated whether they had experienced boredom, depression, family tensions, loss of self-confidence, not enough money, increased difficulty in rearing children, or lack of contact with people as a result of being unemployed. All respondents were asked questions concerning gender equality. Respondents were asked to assess the current work situation for women with respect to wages, job security, promotional opportunities, and the number and variety of jobs available. Respondents were also asked to evaluate reasons why women less often held positions of responsibility and to prioritize areas of action to be taken to remedy existing inequalities. Respondents also rated the impact of women's working on the well-being of men, children, women, families, and couples. Demographic data collected on respondents include gender, age, nationality, marital status, occupation, income, left-right political self-placement, age at completion of education, number of people in household, number of children under 15 in household, subjective size of community, and region of residence.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for electronic and materials science engineering april 2006 in the U.S.

In April 2025, the canton of Zurich had the highest number of registered jobseekers in Switzerland, with over ****** people looking for jobs. This was a **** percent increase compared to the same month in the previous year. The canton of Appenzell Innerrhoden had the smallest number of jobseekers, with only *** registered people. However, this was a ** percent increase compared to the same month in the previous year.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for applied computer science (april 2016) in the U.S.

A survey fielded in the United States in April 2023 found that ** percent of respondents thought that governments should restrict AI's abilities to replace humans in creative and entertainment jobs, such as writers and animators. However, *******5 respondents thought that neither local, nor state, or federal governments should intervene.

This dataset provides a comprehensive view of the job market in California, highlighting companies and cities with the highest number of job opportunities. Created by JoPilot, it contains valuable information for anyone interested in the employment landscape across different industries and regions. It includes key information such as:

• Company name • City • State • Number of active jobs

For job seekers, employers, and researchers, this resource can be particularly useful in several ways:

1. Identifying hot job markets: The data highlights cities with the highest number of job openings, helping job seekers focus their search on areas with more opportunities.
2. Company targeting: By showing which companies have the most active job listings, the dataset allows job seekers to target their applications to organizations that are actively hiring.
3. Industry trends: The information can reveal which industries or sectors are experiencing growth in California, guiding career decisions and educational pursuits.
4. Regional comparisons: Users can compare job markets across different California cities and regions, which is valuable for those considering relocation or analyzing economic trends.
5. Skill alignment: While the dataset doesn't directly provide skill requirements, it can be used alongside other resources to align job seekers' skills with in-demand positions.

For a more comprehensive job search strategy, consider complementing this dataset with additional resources such as the California Labor Market Information tools, which offer detailed insights into wages, employment projections, and industry-specific data.

United States - Unemployment Level - Persons Who Completed Temporary Jobs was 614.00000 Thous. of Persons in April of 2025, according to the United States Federal Reserve. Historically, United States - Unemployment Level - Persons Who Completed Temporary Jobs reached a record high of 1650.00000 in January of 2010 and a record low of 419.00000 in June of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Unemployment Level - Persons Who Completed Temporary Jobs - last updated from the United States Federal Reserve on November of 2025.