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

job_title… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/data-science-job-salaries.

This dataset was obtained from the Google Jobs API through serpAPI and contains information about job offers for data scientists in companies based in the United States of America (USA). The data may include details such as job title, company name, location, job description, salary range, and other relevant information. The dataset is likely to be valuable for individuals seeking to understand the job market for data scientists in the USA and for companies looking to recruit data scientists. It may also be useful for researchers who are interested in exploring trends and patterns in the job market for data scientists. The data should be used with caution, as the API source may not cover all job offers in the USA and the information provided by the companies may not always be accurate or up-to-date.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for data scientist in the U.S.

H-1B visa sponsorship trends for Data Scientist, covering top employers, salary insights, approval rates, and geographic distribution. Explore how job title impacts the U.S. job market under the H-1B program.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for applied scientist ii in the U.S.

Context

I will graduate from my postgraduate study at the University of Exeter in 2021 and want to start my career in London as soon as possible in a data science role.

Those who are seeking jobs like me probably are suffering from which skills should be improved to get a better job. In this context, I scraped the Indeed website and collected information with various queries such as Data Scientist, Data Engineer, Big Data etc. It is scraped around on 2020 July 22th and the information collected are: Job Title, Location, Company Name, Salary, Description.

Content

• indeed-uk.csv: If you want to explore the job market around London, download this one because it aggregates all information and cleans the jobs that are dupliccated.
• all other files: If you want to explore a specific job title, you can download any of them. I tried to separate them into different CSV files however it may contain some noises.

Acknowledgements

Special thanks to Indeed company!

Also thanks to @sl6149 for his similar dataset.

Inspiration

If you have no clue where to start, check my github repository for inspiration.

Possible Questions:

• Who gets hired? What kind of talent do employers want when they are hiring a data scientist?
• Which location has the most opportunities?
• What skills, tools, degrees or majors do employers want the most for data scientists?
• What's the difference between a data scientist, data engineer, and data analyst?
• Can you develop an efficient classification algorithm to differentiate the three job types above?

Explore the progression of average salaries for graduates in Economics Computer Scientist (Equivalent To U.S. Mis Degree) from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Economics Computer Scientist (Equivalent To U.S. Mis Degree) relative to other fields. This data is essential for students assessing the return on investment of their education in Economics Computer Scientist (Equivalent To U.S. Mis Degree), providing a clear picture of financial prospects post-graduation.

Description of the features in dataset:

• work_year: The year in which the salary data was collected (e.g., 2024).
• experience_level: The level of experience of the employee (e.g., MI for Mid-Level).
• employment_type: The type of employment (e.g., FT for Full-Time).
• job_title: The title of the job (e.g., Data Scientist).
• salary: The salary amount.
• salary_currency: The currency in which the salary is denominated (e.g., USD for US Dollars).
• salary_in_usd: The salary amount converted to US Dollars.
• employee_residence: The country of residence of the employee (e.g., AU for Australia).
• remote_ratio: The ratio indicating the level of remote work (0 for no remote work).
• company_location: The location of the company (e.g., AU for Australia).
• company_size: The size of the company (e.g., S for Small).

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for senior data scientist in the U.S.

Graph and download economic data for Employed full time: Wage and salary workers: Computer scientists and systems analysts occupations: 16 years and over: Women (LEU0254690600A) from 2000 to 2010 about analysts, computers, occupation, females, full-time, salaries, workers, 16 years +, wages, employment, and USA.

United States - Employed full time: Wage and salary workers: Medical scientists occupations: 16 years and over: Men was 60.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Medical scientists occupations: 16 years and over: Men reached a record high of 88.00000 in January of 2006 and a record low of 38.00000 in January of 2004. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Medical scientists occupations: 16 years and over: Men - last updated from the United States Federal Reserve on July of 2025.

New Upload:

Added +32,000 more locations. For information on data calculations please refer to the methodology pdf document. Information on how to calculate the data your self is also provided as well as how to buy data for $1.29 dollars.

What you get:

The database contains 32,000 records on US Household Income Statistics & Geo Locations. The field description of the database is documented in the attached pdf file. To access, all 348,893 records on a scale roughly equivalent to a neighborhood (census tract) see link below and make sure to up vote. Up vote right now, please. Enjoy!

Household & Geographic Statistics:

• Mean Household Income (double)
• Median Household Income (double)
• Standard Deviation of Household Income (double)
• Number of Households (double)
• Square area of land at location (double)
• Square area of water at location (double)

Geographic Location:

• Longitude (double)
• Latitude (double)
• State Name (character)
• State abbreviated (character)
• State_Code (character)
• County Name (character)
• City Name (character)
• Name of city, town, village or CPD (character)
• Primary, Defines if the location is a track and block group.
• Zip Code (character)
• Area Code (character)

Abstract

The dataset originally developed for real estate and business investment research. Income is a vital element when determining both quality and socioeconomic features of a given geographic location. The following data was derived from over +36,000 files and covers 348,893 location records.

License

Only proper citing is required please see the documentation for details. Have Fun!!!

Golden Oak Research Group, LLC. “U.S. Income Database Kaggle”. Publication: 5, August 2017. Accessed, day, month year.

Sources, don't have 2 dollars? Get the full information yourself!

2011-2015 ACS 5-Year Documentation was provided by the U.S. Census Reports. Retrieved August 2, 2017, from https://www2.census.gov/programs-surveys/acs/summary_file/2015/data/5_year_by_state/

Found Errors?

Please tell us so we may provide you the most accurate data possible. You may reach us at: research_development@goldenoakresearch.com

for any questions you can reach me on at 585-626-2965

please note: it is my personal number and email is preferred

Check our data's accuracy: Census Fact Checker

Access all 348,893 location records and more:

Don't settle. Go big and win big. Optimize your potential. Overcome limitation and outperform expectation. Access all household income records on a scale roughly equivalent to a neighborhood, see link below:

Website: Golden Oak Research Kaggle Deals all databases $1.29 Limited time only

A small startup with big dreams, giving the every day, up and coming data scientist professional grade data at affordable prices It's what we do.

United States - Employed full time: Wage and salary workers: Physical scientists, all other occupations: 16 years and over was 432.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Physical scientists, all other occupations: 16 years and over reached a record high of 432.00000 in January of 2024 and a record low of 58.00000 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Physical scientists, all other occupations: 16 years and over - last updated from the United States Federal Reserve on August of 2025.

This data collection focuses on persons engaged in the fields of natural science, social science, and engineering as well as in related occupations. The aim of the SSE was to gauge the effects of rapid development and innovation in science and technology during recent years on highly trained scientists and engineers in specific target occupations. Variables in this collection, which encompasses both the original 1982 survey data and data from the 1984 and 1986 follow-ups, include occupation, formal and supplemental education and training, current employment characteristics, job history, annual salary, whether work is supported by United States government funds, funding agency or department, and percentage of time devoted to specific work activities, particularly those that are energy-related. Demographic characteristics supplied include sex, race, Hispanic origin, and marital status.

Graph and download economic data for Employed full time: Wage and salary workers: Physical scientists, all other occupations: 16 years and over: Men (LEU0254588100A) from 2000 to 2024 about occupation, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.

Graph and download economic data for Employed full time: Wage and salary workers: Computer scientists and systems analysts occupations: 16 years and over (LEU0254477000A) from 2000 to 2010 about analysts, computers, occupation, full-time, salaries, workers, 16 years +, wages, employment, and USA.

United States - Employed full time: Wage and salary workers: Biological scientists occupations: 16 years and over: Men was 45.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Biological scientists occupations: 16 years and over: Men reached a record high of 66.00000 in January of 2006 and a record low of 37.00000 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Biological scientists occupations: 16 years and over: Men - last updated from the United States Federal Reserve on July of 2025.

Graph and download economic data for Employed full time: Wage and salary workers: Medical scientists occupations: 16 years and over: Women (LEU0254694400A) from 2000 to 2024 about medical, occupation, females, full-time, salaries, workers, 16 years +, wages, employment, and USA.

Graph and download economic data for Employed full time: Wage and salary workers: Chemists and materials scientists occupations: 16 years and over: Men (LEU0254587900A) from 2000 to 2024 about chemists, occupation, materials, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.

Graph and download economic data for Employed full time: Wage and salary workers: Agricultural and food scientists occupations: 16 years and over: Women (LEU0254694100A) from 2000 to 2024 about occupation, females, full-time, agriculture, salaries, workers, food, 16 years +, wages, employment, and USA.