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US and International IT Salary Benchmarks
Data Science and Analytics
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About
Explore the salary and experience landscape of the technology industry, offering an in-depth look at US and international pay structures. The data originates from a publicly shared questionnaire collected by Hacker News in 2016. This resource has been refined and provides insight into pay rates, geographical relevance, various job titles and their categories, along with details regarding experience levels and potential bonuses. It serves as a valuable resource for guiding career aspirants and understanding typical compensation at large employers, such as Google or Amazon.
Columns
The dataset contains 17 fields detailing professional and compensation attributes, stored in the
salaries_clean.csv file:employer_name: The name of the employer (String).location_name: The city or location where the respondent is based (String).location_state: The state associated with the location (String).location_country: The country associated with the location (String).location_latitude: The latitude coordinate for the location (Float).location_longitude: The longitude coordinate for the location (Float).job_title: The specific role of the respondent (String). The most common entry is 'software engineer'.job_title_category: The broader category the role belongs to (String). Over half of the entries fall under the 'Software' category.job_title_rank: The seniority rank of the job title (Integer).total_experience_years: The respondent's total professional experience (Integer). The average is approximately 6.76 years.employer_experience_years: Experience accumulated with the current employer (Integer). The average is approximately 2.66 years.annual_base_pay: The respondent's annual base pay (Integer).signing_bonus: Any signing bonus received (Integer).annual_bonus: Any annual performance bonus received (Integer).stock_value_bonus: The stock value bonus received (Integer).comments: Additional comments provided by the respondent (String).submitted_at: Date and time the survey was submitted (DateTime).
Distribution
The data is provided in a single CSV file named
salaries_clean.csv, which is 208.62 kB in size and contains 19 fields. The dataset generally contains 1,655 records. However, several fields, particularly those relating to geographical details like location state and country, have a high percentage of missing values (e.g., location state is 66% missing). Submission dates are concentrated between 21 March 2016 and 23 March 2016.Usage
This data supports various analytical activities focused on the technology employment sector. Users can employ techniques such as k-means clustering to segment workers based on similar wage levels. Visualization methods, including box plots and histograms, can effectively illustrate salary discrepancies between different employers and job roles. The data is also suited for:
- Geospatial Analysis: Uncovering geographical trends, identifying clusters of tech activity, and differentiating expected salaries by city or region using the provided location coordinates.
- Career Path Modeling: Assessing career progression by grouping job title categories (e.g., developers versus operations) and correlating them with experience parameters to build statistical prediction models.
- Equity Research: Analyzing salary differences, including potential compensation inequalities related to gender, by leveraging information found within the comments section.
- Reporting: Generating insightful charts and graphs that paint a clear picture of salary trends for stakeholders.
Coverage
The dataset focuses primarily on salary and experience data collected across US and international regions. Specific locations frequently mentioned include San Francisco and Seattle. While the data captures submissions from multiple countries, a large portion of the geographical data is missing. The temporal scope is extremely limited, capturing submissions exclusively during a three-day window in March 2016.
License
CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
Who Can Use It
Intended users include:
- Job Seekers and Career Changers: Individuals evaluating new roles or aiming to land a job in the tech sector, using the insights to benchmark expected pay.
- HR Professionals and Recruiters: People determining appropriate compensation structures and understanding market rates for various job titles.
- Data Scientists and Academics: Researchers conducting quantitative analysis on labour economics, career paths, and demographic salary trends within the tech industry.
- Business Strategists: Those looking to understand competitive pay landscapes among major technology employers.
Dataset Name Suggestions
- 2016 Tech Salary and Experience Data
- Hacker News Global Tech Compensation Survey
- US and International IT Salary Benchmarks
Attributes
Original Data Source: US and International IT Salary Benchmarks
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