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Global AI ML DS Jobs Data
Data Science and Analytics
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About
Data on AI, ML, DS & Big Data Jobs is a valuable collection of information detailing job opportunities across the fields of Artificial Intelligence (AI), Machine Learning (ML), Data Science (DS), and Big Data. It provides insights into various aspects, including company names, job titles, geographical locations, job types (such as full-time or remote), required experience levels, salary expectations, job requirements, and available facilities. This dataset offers significant insights for job seekers, researchers, and organisations keen on understanding these rapidly evolving domains. By analysing the data, users can better understand job market trends, the geographical spread of opportunities, popular job titles, necessary skills and qualifications, salary expectations, and the types of benefits provided by companies in these areas. It serves as a valuable resource for extracting meaningful insights and supporting informed decisions within the dynamic world of AI, ML, DS, and Big Data jobs.
Columns
- Company: Lists the names of organisations offering data science positions, revealing the diverse range of employers in the field. Publicis Groupe is a frequently listed company, making up 4% of entries, while Bosch Group accounts for 3% of entries.
- Job Title: Specifies the various job titles associated with each position, helping users understand the different roles available within the data science domain. Common titles include Data Engineer (3%) and Data Scientist (3%).
- Location: Indicates the geographical location of each job opportunity, enabling individuals to identify job prospects in specific regions or countries. Bengaluru, India, is a common location (3%), followed by Paris, France (2%).
- Job Type: Classifies the nature of job roles, such as full-time, part-time, or remote. This assists job seekers in understanding the flexibility and nature of positions. Full-time roles represent 97% of entries, with internships at 2%.
- Experience level: Shows the desired experience level for each job, helping applicants assess their suitability. Senior-level positions are the most frequent, accounting for 59% of the valid entries, while entry-level roles make up 16%.
- Salary: Provides information about the expected salary range or compensation package, allowing candidates to gauge the financial aspects of roles. Common salary indications include 115K+ (8%) and 62K+ (7%).
- Requirment of the company: Highlights specific skills, qualifications, and prerequisites sought by companies. It offers insights into the expertise required for data science roles. A common combination of requirements includes Big Data, Business Intelligence, Data analysis, EDA, Excel, and Machine Learning.
- Facilities: Outlines additional benefits or perks offered by companies, such as healthcare benefits, flexible working hours, or professional development opportunities. This gives job seekers a glimpse into the extra advantages provided by employers.
Distribution
The dataset is provided in CSV format, specifically as
data_science_job.csv, and has a size of 667.99 kB. It features 8 distinct columns. The data includes approximately 3198 records for most columns. For instance, the 'Company', 'Job Title', 'Location', and 'Job Type' columns each have 3197 valid entries with only 1 missing entry. The 'Experience level' column has 2962 valid entries, with 236 missing, and 'Salary' has 3009 valid entries, with 189 missing. The 'Requirment of the company' and 'Facilities' columns both have 3198 valid entries with no missing data. The dataset is expected to be updated monthly.Usage
This dataset is ideal for:
- Job seekers: Exploring career prospects and understanding job market demands in AI, ML, DS, and Big Data.
- Researchers: Conducting market research on industry trends, geographical distribution of roles, and salary benchmarks.
- Organisations: Building predictive models for recruitment, talent acquisition, or market analysis.
- Academics: Analysing popular job titles, required skills, and qualifications within these tech fields.
- Policy Makers: Understanding employment trends and skills gaps in the technology sector.
Coverage
The dataset has a global geographical scope, with specific locations such as Bengaluru, India (3%) and Paris, France (2%) being frequently represented. The data focuses on job opportunities within Artificial Intelligence, Machine Learning, Data Science, and Big Data domains. It includes a range of experience levels, with a notable emphasis on senior-level positions (59%) and a significant portion of entry-level roles (16%). The dataset is designed to reflect the rapidly evolving nature of these fields, with an expected monthly update frequency. No specific time range for the current snapshot of data is provided, but its regular updates ensure currency.
License
CC0: Public Domain
Who Can Use It
- Data scientists and machine learning engineers: To gain insights into available job opportunities and requirements.
- Aspiring professionals: To understand career paths, necessary skills, and salary expectations in AI, ML, DS, and Big Data.
- HR professionals and recruiters: For market intelligence on hiring trends, competitor analysis, and salary benchmarking.
- Education and training providers: To tailor curricula to match industry demands and required skill sets.
- Economists and analysts: To study labour market dynamics and economic indicators within the tech sector.
Dataset Name Suggestions
- Global AI ML DS Jobs Data
- Tech Career Market Insights
- Data Science Employment Trends
- Big Data Job Opportunities Dataset
- AI & ML Roles Worldwide
Attributes
Original Data Source: Global AI ML DS Jobs Data
QUALITY