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United States Machine Learning Vacancy Records
Data Science and Analytics
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About
Capturing the evolving landscape of artificial intelligence recruitment across the United States, these records provide a detailed look at 1,000 machine learning vacancies spanning late 2024 to early 2025. By aggregating information from official career portals and major job boards, the collection offers a representative view of current hiring practices and workforce requirements. It serves as a vital resource for mapping the future of AI employment, allowing for deep insights into skill demands and organisational missions during a pivotal technological shift.
Columns
- ID: A unique numerical identifier assigned to each individual job posting for tracking purposes.
- job_posted_date: The specific date the vacancy was published, presented in a standard YYYY-MM-DD format.
- company_address_locality: The specific city or town where the hiring organisation is located.
- company_address_region: The state or geographic region associated with the company's physical address.
- company_name: The official name of the business or entity seeking to fill the position.
- company_description: A brief overview of the hiring employer’s industry focus, mission, or corporate culture.
- job_description_text: The full, unfiltered text of the job advertisement, containing details on responsibilities and required tools.
- seniority_level: The professional experience tier targeted by the role, ranging from internships to mid-senior level positions.
- job_title: The specific designation used in the posting, such as Machine Learning Engineer or AI Specialist.
Distribution
The data is delivered in a CSV format titled
Job_Postings_US new.csv, with a total file size of 5.37 MB. It consists of 1,000 records across 9 distinct columns, maintaining a high level of integrity with nearly 100% validity across all primary fields. The resource holds a maximum usability score of 10.00 and is intended for annual updates to reflect the latest market conditions.Usage
This collection is ideal for performing natural language processing (NLP) tasks, such as automated skill extraction and the development of skill-demand models. It can be utilised to identify regional hiring hotspots within the United States and to conduct temporal analyses of seasonal hiring cycles. Analysts can also use the data for benchmarking recruitment trends and forecasting professional career paths within the technology sector.
Coverage
The geographic scope spans the entire United States, with notable concentrations in urban hubs such as San Francisco and Los Angeles. Temporally, the records cover a period from late 2022 through to April 2025, providing a focused snapshot of the post-AI boom surge. The demographic scope captures professional roles from various experience levels across nearly 500 unique hiring organisations.
License
CC0: Public Domain
Who Can Use It
Labour market researchers and policy advisors can utilise these metrics to assess the impact of AI on the national workforce. Data scientists can leverage the raw job descriptions to train and test machine learning models for text classification. Additionally, career coaches and job seekers can gain insights into the specific technical proficiencies currently valued by top-tier technology employers.
Dataset Name Suggestions
- US Machine Learning Job Market Index (2024-2025)
- American AI Recruitment and Skill Demand Registry
- ML Career Path and Workforce Analytics Database
- United States Machine Learning Vacancy Records
Attributes
Original Data Source:United States Machine Learning Vacancy Records
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