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AI/ML Professional Salaries Dataset
Natural Language Processing
Tags and Keywords
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Free
About
This dataset provides detailed insights into salaries for various job roles within the data science domain. It captures information crucial for understanding compensation trends, work arrangements, and company specifics across different experience levels and geographical locations. The data aims to illuminate the salary landscape for data professionals, offering a valuable resource for market analysis and career planning.
Columns
- work_year: The specific year in which the salary was paid.
- experience_level: Denotes the level of experience required for the job during that year, including Entry-level / Junior (EN), Mid-level / Intermediate (MI), Senior-level / Expert (SE), and Executive-level / Director (EX).
- employment_type: Specifies the type of employment for the role, such as Part-time (PT), Full-time (FT), Contract (CT), or Freelance (FL).
- job_title: The particular role undertaken during the year.
- salary: Represents the total gross salary amount paid in its original currency.
- salary_currency: The currency of the salary paid, identified by its ISO 4217 currency code.
- salary_in_usd: The salary converted to US Dollars, calculated using an FX rate divided by the average USD rate for the respective year.
- employee_residence: The primary country of residence of the employee during the work year, indicated by an ISO 3166 country code.
- remote_ratio: Indicates the overall proportion of work performed remotely, with possible values including 0 (No remote work, less than 20%), 50 (Partially remote), and 100 (Fully remote, more than 80%).
- company_location: The country where the employer's main office or contracting branch is situated, identified by an ISO 3166 country code.
- company_size: The average number of individuals employed by the company during the year, categorised as S (less than 50 employees - small), M (50 to 250 employees - medium), or L (more than 250 employees - large).
Distribution
The dataset is provided in CSV format and totals approximately 36.96 KB. It comprises 607 records, with no missing values observed across its twelve columns. Data distributions vary per column, for instance, a significant portion of salaries are within the lower to mid-ranges, and most job entries are Full-time.
Usage
This dataset is ideal for:
- Salary Benchmarking: Comparing data science salaries across different experience levels, job titles, and company sizes.
- Career Planning: Analysing salary trends and typical compensation for specific roles to inform career progression decisions.
- Market Analysis: Understanding geographical variations in data science salaries and the prevalence of remote work.
- Recruitment Strategy: Aiding companies in setting competitive salary ranges for data science positions.
- Academic Research: Supporting studies on labour market dynamics within the technology and data sectors.
Coverage
The dataset covers job salaries primarily from 2020 to 2022. Geographically, the data includes employee residences and company locations from numerous countries, with the United States being the most frequently represented (55% for employee residence, 58% for company location). The United Kingdom also features prominently. The data encompasses various demographic aspects such as experience levels (Entry to Executive), employment types (Full-time being dominant at 97%), job titles (Data Scientist and Data Engineer being most common), and company sizes (Medium-sized companies representing 54%). Remote work ratios are also covered, showing a high proportion of fully remote positions.
License
CC0: Public Domain
Who Can Use It
- Data Scientists & Analysts: For personal salary comparisons and career trajectory insights.
- HR Professionals & Recruiters: To inform salary negotiations and talent acquisition strategies for data roles.
- Job Seekers: To understand typical compensation for data science roles globally.
- Researchers & Academics: For studies on workforce trends, compensation models, and the evolution of the data science industry.
- Organisations: To gain insights into competitive compensation structures and remote work trends within the data science field.
Dataset Name Suggestions
- Data Science Salaries 2020-2022
- Global Data Science Compensation Insights
- AI/ML Professional Salaries Dataset
- Tech Industry Salaries & Remote Work Analysis
- Data Professional Earnings Overview
Attributes
Original Data Source: AI/ML Professional Salaries Dataset
QUALITY