This Dataset containes the details of the AI, ML, Data Science Salary (2020- 2025). Salary data is in USD and recalculated at its average fx rate during the year for salaries entered in other currencies.

The data is processed and updated on a weekly basis so the rankings may change over time during the year.

Attribute Information

• 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: The role worked in during the year.
• salary: The total gross salary amount paid.
• salary_currency: The currency of the salary paid as an ISO 4217 currency code.
• salary_in_usd: The salary in USD (FX rate divided by avg. USD rate of respective year) via statistical data from the BIS and central banks.
• employee_residence: Employee's primary country of residence in during the work year as an ISO 3166 country code.
• remote_ratio : The overall amount of work done remotely, possible values are as follows: 0 No remote work (less than 20%) 50 Partially remote/hybird 100 Fully remote (more than 80%)
• company_location: The country of the employer's main office or contracting branch as an ISO 3166 country code.
• company_size: The average number of people that worked for the company during the year: S less than 50 employees (small) M 50 to 250 employees (medium) L more than 250 employees (large)

Acknowledgements

https://aijobs.net/

Photo by Anastassia Anufrieva on Unsplash

Texas public school district superintendent salary information as of October 2024.

🚀 Data Science Careers in 2025: Jobs and Salary Trends in Pakistan 🚀 Data Science is one of the fastest-growing fields, and by 2025, the demand for skilled professionals in Pakistan will only increase. If you’re considering a career in Data Science, here’s what you need to know about the top jobs and salary trends.

🔍 Top Data Science Jobs in 2025 1) Data Scientist Avg Salary: PKR 1.2M - 2.5M/year (Entry-Level), PKR 3M - 6M/year (Experienced) Skills: Python, R, Machine Learning, Data Visualization

2) Data Analyst Avg Salary: PKR 800K - 1.5M/year (Entry-Level), PKR 2M - 3.5M/year (Experienced) Skills: SQL, Excel, Tableau, Power BI

3) Machine Learning Engineer Avg Salary: PKR 1.5M - 3M/year (Entry-Level), PKR 4M - 7M/year (Experienced) Skills: TensorFlow, PyTorch, Deep Learning, NLP

4)Business Intelligence Analyst Avg Salary: PKR 1M - 2M/year (Entry-Level), PKR 2.5M - 4M/year (Experienced) Skills: Data Warehousing, ETL, Dashboarding

5) AI Research Scientist Avg Salary: PKR 2M - 4M/year (Entry-Level), PKR 5M - 10M/year (Experienced) Skills: AI Algorithms, Research, Advanced Mathematic

💡 Why Choose Data Science? High Demand: Every industry in Pakistan needs data professionals. Attractive Salaries: Competitive pay based on technical expertise. Growth Opportunities: Unlimited career growth in this field.

📈 Salary Trends Entry-Level: PKR 800K - 1.5M/year Mid-Level: PKR 2M - 4M/year Senior-Level: PKR 5M+ (depending on expertise and industry)

🛠️ How to Get Started? Learn Skills: Focus on Python, SQL, Machine Learning, and Data Visualization. Build Projects: Work on real-world datasets to create a strong portfolio. Network: Connect with industry professionals and join Data Science communities.

work_year: The year in which the data was recorded. This field indicates the temporal context of the data, important for understanding salary trends over time.

job_title: The specific title of the job role, like 'Data Scientist', 'Data Engineer', or 'Data Analyst'. This column is crucial for understanding the salary distribution across various specialized roles within the data field.

job_category: A classification of the job role into broader categories for easier analysis. This might include areas like 'Data Analysis', 'Machine Learning', 'Data Engineering', etc.

salary_currency: The currency in which the salary is paid, such as USD, EUR, etc. This is important for currency conversion and understanding the actual value of the salary in a global context.

salary: The annual gross salary of the role in the local currency. This raw salary figure is key for direct regional salary comparisons.

salary_in_usd: The annual gross salary converted to United States Dollars (USD). This uniform currency conversion aids in global salary comparisons and analyses.

employee_residence: The country of residence of the employee. This data point can be used to explore geographical salary differences and cost-of-living variations.

experience_level: Classifies the professional experience level of the employee. Common categories might include 'Entry-level', 'Mid-level', 'Senior', and 'Executive', providing insight into how experience influences salary in data-related roles.

employment_type: Specifies the type of employment, such as 'Full-time', 'Part-time', 'Contract', etc. This helps in analyzing how different employment arrangements affect salary structures.

work_setting: The work setting or environment, like 'Remote', 'In-person', or 'Hybrid'. This column reflects the impact of work settings on salary levels in the data industry.

company_location: The country where the company is located. It helps in analyzing how the location of the company affects salary structures.

company_size: The size of the employer company, often categorized into small (S), medium (M), and large (L) sizes. This allows for analysis of how company size influences salary.

Wages in the United States increased 4.72 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset includes recommended positions and salaries for 2025 by title (without names) and salary. The dataset is excerpted from the 2025 Budget Recommendations, which is the line-item budget proposed by the Mayor to the City Council for approval. Disclaimer: the “Total Budgeted Unit” column displays either A) the number of employees AND vacancies associated with a given position, or B) the number of budgeted units (ie. hours/months) for that position. “Position Control” determines whether Total Budgeted Units column will count employees and vacancies or hours/months. If a Position Control is 1, then employees and vacancies are displayed; if a Position Control is 0, then the total number of hours/months recorded is displayed. This dataset follows the format of the equivalent datasets from past years except that Division Code, Section Code, Subsection Code, and Position Control have changed from Number to Text (not all in the same year) in order to accommodate non-numeric values. For more information about the budget process, visit the Budget Documents page: https://www.chicago.gov/city/en/depts/obm/provdrs/budget.html.

In 2025, the highest-paid baseball players in South Korea were Kim Kwang-hyun and Mel Rojas Jr. according to data from the Korea Baseball Organization (KBO). Their annual salary was approximately three and 2.52 billion South Korean won, respectively.Professional baseball in South Korea Naturally, not all professional baseball players are as well paid as Ryu Hyun-Jin or the other top players, who receive more than a billion won per annum. In fact, Ryu’s team, the Hanwha Eagles, paid an average of 163.35 million won in 2024, which was a bit more than the league average. The ticket revenue of KBO matches in 2023 was approximately 123.3 billion won. Many spectators would go to watch games with friends and family. As the most popular professional sport in South Korea, the attendance numbers for baseball matches in the country look set to continue to increase. The KBO League Among the various professional sports in South Korea, baseball was the most popular according to respondents to a survey. The KBO League offers the highest level of pro baseball in the country, and earning a spot on a team's roster is an impressive feat. The Kia Tigers are the most successful team overall, winning the most championships throughout the league's history which spans over 40 years. During the 2023 season, the LG Twins had the highest win rates in the league, with the team going on to win the championship.

According to a salary budget planning survey conducted in the Asia-Pacific region, companies in India experienced the highest salary increase, at *** percent, in 2023. The country's salary growth rate was projected to remain the highest among the surveyed countries in the region in 2025, at around *** percent.

A structured overview of the average, net, median, and minimum wage in Germany for 2025. This dataset combines original market research conducted by KUMMUNI GmbH with publicly available data from the German Federal Statistical Office. It includes values with and without bonuses, hourly minimum wage, and take-home pay after tax.

The payroll data represents the amount paid to an employee during the reported time period. In addition to regular pay, these amounts may include other pay types such as overtime, longevity, shift differential or terminal pay. This amount does not include any state share costs associated with the payroll i.e. FICA, state share retirement, etc. This amount may vary from an employee’s ‘salary’ due to pay adjustments or pay period timing. The payroll information will be updated monthly after the end of the month. For example, July information will be added in August after the 15th of the month.

City employee base salary as of 2025-01-14.

The 2025 data provides base salaries for every position's compensation. The data represents a snapshot of base salaries for all employees as of 2025-01-14 for the City of Fort Collins in an hourly rate or annual salary format for 2025 rather than a forecasted amount of actual salary payments for 2025. Personnel spending data can be found on openbook.fcgov.com

Player salaries for all 30 Major League teams for 2011 through 2024 seasons. Data includes salaries for active players and players on the Major League injured list.

The data for this project was sourced from Spotrac, accessed on January 9, 2025. Spotrac provides detailed information on player contracts, salaries, and other financial data for professional sports.

Data Science Job Salaries Dataset contains 11 columns, each are:

work_year: The year the salary was paid. experience_level: The experience level in the job during the year employment_type: The type of employment for the role job_title: The role worked in during the year. salary: The total gross salary amount paid. salary_currency: The currency of the salary paid as an ISO 4217 currency code. salaryinusd: The salary in USD employee_residence: Employee's primary country of residence in during the work year as an ISO 3166 country code. remote_ratio: The overall amount of work done remotely company_location: The country of the employer's main office or contracting branch company_size: The median number of people that worked for the company during the year

A comprehensive dataset of top occupations for H-1B Visa sponsorships in 2025, including salary data, petition trends, and employer insights. Updated annually with the latest trends and employer behavior regarding H-1B visa sponsorship.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for business administration (major statistics) in the U.S.

Data measure usual weekly earnings of wage and salary workers. Wage and salary workers are workers who receive wages, salaries, commissions, tips, payment in kind, or piece rates. The group includes employees in both the private and public sectors but, for the purposes of the earnings series, it excludes all self-employed persons, both those with incorporated businesses and those with unincorporated businesses. Usual weekly earnings represent earnings before taxes and other deductions and include any overtime pay, commissions, or tips usually received (at the main job in the case of multiple jobholders). Prior to 1994, respondents were asked how much they usually earned per week. Since January 1994, respondents have been asked to identify the easiest way for them to report earnings (hourly, weekly, biweekly, twice monthly, monthly, annually, or other) and how much they usually earn in the reported time period. Earnings reported on a basis other than weekly are converted to a weekly equivalent. The term "usual" is determined by each respondent's own understanding of the term. If the respondent asks for a definition of "usual," interviewers are instructed to define the term as more than half the weeks worked during the past 4 or 5 months. For more information see https://www.bls.gov/cps/earnings.htm

The series comes from the 'Current Population Survey (Household Survey)'

The source code is: LES1252881900

Data measure usual weekly earnings of wage and salary workers. Wage and salary workers are workers who receive wages, salaries, commissions, tips, payment in kind, or piece rates. The group includes employees in both the private and public sectors but, for the purposes of the earnings series, it excludes all self-employed persons, both those with incorporated businesses and those with unincorporated businesses. Usual weekly earnings represent earnings before taxes and other deductions and include any overtime pay, commissions, or tips usually received (at the main job in the case of multiple jobholders). Prior to 1994, respondents were asked how much they usually earned per week. Since January 1994, respondents have been asked to identify the easiest way for them to report earnings (hourly, weekly, biweekly, twice monthly, monthly, annually, or other) and how much they usually earn in the reported time period. Earnings reported on a basis other than weekly are converted to a weekly equivalent. The term "usual" is determined by each respondent's own understanding of the term. If the respondent asks for a definition of "usual," interviewers are instructed to define the term as more than half the weeks worked during the past 4 or 5 months. For more information see https://www.bls.gov/cps/earnings.htm

The series comes from the 'Current Population Survey (Household Survey)'

The source code is: LES1252881500

Data measure usual weekly earnings of wage and salary workers. Wage and salary workers are workers who receive wages, salaries, commissions, tips, payment in kind, or piece rates. The group includes employees in both the private and public sectors but, for the purposes of the earnings series, it excludes all self-employed persons, both those with incorporated businesses and those with unincorporated businesses. Usual weekly earnings represent earnings before taxes and other deductions and include any overtime pay, commissions, or tips usually received (at the main job in the case of multiple jobholders). Prior to 1994, respondents were asked how much they usually earned per week. Since January 1994, respondents have been asked to identify the easiest way for them to report earnings (hourly, weekly, biweekly, twice monthly, monthly, annually, or other) and how much they usually earn in the reported time period. Earnings reported on a basis other than weekly are converted to a weekly equivalent. The term "usual" is determined by each respondent's own understanding of the term. If the respondent asks for a definition of "usual," interviewers are instructed to define the term as more than half the weeks worked during the past 4 or 5 months. For more information see https://www.bls.gov/cps/earnings.htm

The series comes from the 'Current Population Survey (Household Survey)'

The source code is: LEU0252882500

Philippines Employment: Wage & Salary Workers: With Pay in Own Family Business data was reported at 211.000 Person th in Feb 2025. This records an increase from the previous number of 106.000 Person th for Jan 2025. Philippines Employment: Wage & Salary Workers: With Pay in Own Family Business data is updated monthly, averaging 160.500 Person th from Jan 2021 (Median) to Feb 2025, with 50 observations. The data reached an all-time high of 312.000 Person th in Nov 2022 and a record low of 76.000 Person th in Dec 2024. Philippines Employment: Wage & Salary Workers: With Pay in Own Family Business data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G025: Labour Force Survey: Employment: by Industry, Occupation and Class.

Wages in the United States increased to 31.18 USD/Hour in May from 31.06 USD/Hour in April of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2025, the average salary of a graduate from the Tsinghua University School of Economics and Management in China with low work experience was 225,947 U.S. dollars (once adjusted for purchasing power parity). This was the highest in the world, ahead of students from the Shanghai Institute of Finance at Shanghai Jiao Tong University and HEC Paris. Salaries of MBA graduates The salaries of business school MBA graduates worldwide stood at 120,000 U.S. dollars in 2024, while graduates who held a bachelor’s degree could expect a starting salary of 69,000 U.S. dollars. The largest university worldwide is located in Africa The university with the highest number of students in the world is found in Nigeria. Ambrose Alli University has more than 536,000 registered students. Tribhuvan University in Nepal and Payame Noor University in Iran round up the top three.