Data Description
The AI & Data Job Salaries and Skills Dataset 2024-2025 is synthetically prepared and provides a detailed, global overview of job listings in artificial intelligence, data science, machine learning, and related fields. This dataset aggregates job postings from October 2024 to July 2025, capturing a wide spectrum of roles, required skills, compensation, and organizational attributes across multiple countries and industries.
With over 15,000 entries, each record details the job title, salary (in USD and local currency), experience level, employment type, company location and size, remote work ratio, required technical skills, education and experience requirements, industry, posting and application dates, job description length, benefits score, and company name. This rich dataset is designed for data scientists, career analysts, HR professionals, and researchers interested in AI workforce trends, salary benchmarking, and skills demand analysis.
Column Details
| Column Name | Description | Example Values |
|---|---|---|
| job_id | Unique identifier for each job posting | AI00001, AI00002 |
| job_title | Title/role advertised | AI Research Scientist, Data Analyst |
| salary_usd | Annual salary converted to USD | 90376, 124355 |
| salary_currency | Currency in which salary is offered | USD, EUR, GBP |
| experience_level | Level of experience required (EN=Entry, MI=Mid, SE=Senior, EX=Executive) | SE, EN, MI, EX |
| employment_type | Contract type (CT=Contract, FT=Full-time, PT=Part-time, FL=Freelance) | FT, PT, CT, FL |
| company_location | Country where the company is based | China, Canada, Germany |
| company_size | Company size (S=Small, M=Medium, L=Large) | S, M, L |
| employee_residence | Country of employee residence | China, Ireland, Singapore |
| remote_ratio | % of remote work allowed (0=Onsite, 50=Hybrid, 100=Remote) | 0, 50, 100 |
| required_skills | Key technical skills required (comma-separated) | Python, SQL, Tableau, Docker |
| education_required | Minimum education level required | Bachelor, Master, PhD, Associate |
| years_experience | Minimum years of experience required | 0, 4, 9, 15 |
| industry | Industry sector of the job | Automotive, Media, Healthcare |
| posting_date | Date when the job was posted (YYYY-MM-DD) | 2024-10-18 |
| application_deadline | Last date to apply for the job (YYYY-MM-DD) | 2024-11-07 |
| job_description_length | Length of job description in characters | 1076, 2340 |
| benefits_score | Numeric score (0-10) reflecting benefits quality | 5.9, 9.4 |
| company_name | Name of the hiring company | Smart Analytics, TechCorp Inc |
Example Data Row (Landscape Format)
| Field | Value |
|---|---|
| job_id | AI00001 |
| job_title | AI Research Scientist |
| salary_usd | 90376 |
| salary_currency | USD |
| experience_level | SE |
| employment_type | CT |
| company_location | China |
| company_size | M |
| employee_residence | China |
| remote_ratio | 50 |
| required_skills | Tableau, PyTorch, Kubernetes, Linux, NLP |
| education_required | Bachelor |
| years_experience | 9 |
| industry | Automotive |
| posting_date | 2024-10-18 |
| application_deadline | 2024-11-07 |
| job_description_length | 1076 |
| benefits_score | 5.9 |
| company_name | Smart Analytics |
Short Form Usage :
- Experience Level: EN (Entry), MI (Mid), SE (Senior), EX (Executive).
- Employment Type: FT (Full-time), PT (Part-time), CT (Contract), FL (Freelance).
- Company Size: S (Small), M (Medium), L (Large).
- Remote Ratio: 0 (On-site), 50 (Hybrid), 100 (Remote).
Key Features
- Global Coverage: Jobs span North America, Europe, Asia, and beyond.
- Comprehensive Role Types: Includes AI researchers, ML engineers, data analysts, product managers, and more.
- Salary Benchmarking: Salaries in USD and local currencies, with company size and location context.
- Skills Mapping: Tracks in-demand skills (Python, SQL, NLP, cloud, MLOps, etc.) for each role.
- Remote Work Insights: Quantifies remote/hybrid/onsite opportunities.
- Education & Experience: Minimum qualifications and years of experience required.
- Industry Trends: Sector-wise breakdown for cross-industry analysis.
Use Cases
- Salary Analysis: Benchmark compensation across roles, countries, and industries.
- Skills Demand: Identify trending and essential skills for AI/data roles.
- Workforce Planning: Guide talent acquisition, upskilling, and organizational strategy.
- Career Research: Inform job seekers about requirements and market trends.
- Visualization & Modeling: Ideal for EDA, dashboards, and predictive analytics.
Verification Report
The following data verification reports are provided by the seller:
