Introduction
Data Sources and Analytical Tools
This data story relies on the dataset which is based on real-world data and covers Data Science, Artificial Intelligence, and Machine Learning job listings from 2020 to 2025 hosted on Kaggle. It has been curated and uploaded to Kaggle by Adil Shamim: https://www.kaggle.com/datasets/adilshamim8/salaries-for-data-science-jobs. Data sources are AIJobs salary survey (CC0 license), 365DataScience, Payscale, KDnuggets, ZipRecruiter, and others.
Tableau is used for all data visualizations with “filtering” and “calculation field” features. Each visualization is located into its own tab for the public view.
Chapter 1 (Ch.1): Countries with Job Opening(s) – Uneven distribution in the world
On the world map, there're 97 countries with at least 1 job opening. If we consider there are 195 countries in the world, half of the world countries are not even looking for a Data Science professional. We could observe the economically developed and emerging countries are in the loop. Meanwhile low-income countries or countries having conflict/war are mostly not having a single job opening.
United States is clear leader in the posting of AI-related jobs with over 135k job openings in between 2020 to 2025.
Chapter 2 (Ch.2): What are the most wanted roles? – Practitioners lead the way
Amongst 422 job titles, the ones with the practitioner skills are preferred more like Data Scientist, Data Analyst and Data Engineer. This highlights the need for Data Science, Artificial Intelligence, and Machine Learning talents who will design, build up, run and maintain data science projects with hands-on experience.
Chapter 3 (Ch.3): What is the trend of years in between 2020-2025? – Foundational roles are the most wanted, new roles emerged
In the Sankey diagram, some titles — such as Data Analyst and Data Scientist — are spread across multiple years; both are considered foundational roles in the field of data science. The rationale behind that could be explained as whenever the roles were available in prior years are continued by leading the number of job listings as we see in Chapter 2. New specific titles like “AI Engineer” started its appearance by 2022 and showed a significant spike from only 1 listing and reached to 1394 listings by 2025.
Conclusion
The United States is leading the world in AI-related job listings, while many developing nations have a scarcity of such opportunities, with some having none at all. Great Britain and Europe are also engaged but significantly behind in the "job listings race". This highlights a significant disparity between the leading nation and the rest of the world.
Foundational titles like “Data Scientist” and practitioner related titles are leading the jobs as data collection, preparation and designing models take most of the time in the field. This also indicates the interest of companies in which they would like to analyze customer feedback, run predictions, make forecasts or detect anomalies within broader data science practices encompassing methodologies from Machine Learning and Artificial Intelligence. As highlighted in Chapter 3, the exponential growth of emerging AI-specific job titles like "AI Engineer" proves that companies are highly interested in AI talent by 2025. In the near future, I do not expect this to change, instead it is likely to create even more new job opportunities together with new AI-related job titles.
As a result, the US is the leading market for AI professionals, offering a high volume of job opportunities. This is followed by Europe, where the AI job market is also expanding. While demand exists for both foundational and emerging roles, the latter is seeing exponential growth in job listings, indicating a shift in the market toward newer, specialized practitioner positions.
Sertaç Levent
Founder, Vubion.ai