Artificial intelligence job postings related to machine learning and data science increased this year, according to Indeed.
Postings for jobs in artificial intelligence (AI) rose 29% in the last year, from May 2018 to May 2019, according to new data from job search site Indeed. However, this represents a significant decrease from years past: From May 2017 to May 2018, AI job postings on the site grew nearly 58%, and from May 2016 to May 2017, they grew 136%.
Job seeker interest in AI-related positions is also beginning to slow, Indeed researchers noted in a Friday blog post: Searches for AI-related jobs on Indeed decreased by nearly 15% in the last year, while they had increased 32% and 49% the previous two years. The drop suggests there may be more open jobs than there are qualified employees to fill them, the post noted.
In terms of most in-demand AI jobs, the following 10 positions had the highest percentage of job descriptions that included the keywords “artificial intelligence” or “machine learning,” according to Indeed:
- Machine Learning Engineer
- Deep Learning Engineer
- Senior Data Scientist
- Computer Vision Engineer
- Data Scientist
- Algorithm Developer
- Junior Data Scientist
- Developer Consultant
- Director of Data Science
- Lead Data Scientist
While machine learning engineers had the highest percentage of AI and machine learning keyboards both this year and, several of these in-demand roles were not found on the 2018 list, the post noted. For example, this is the first time deep learning engineer has appeared on the list, let alone in second place. Senior and junior data scientist, developer consultant, director of data science, and lead data scientists are also new to the list this year.
Meanwhile, director of analytics, statistician, principal scientist, and data engineer roles did not make it from 2018 to 2019.
These year-over-year changes could be a sign of growing demand for data scientists across all companies and industries, the post noted. While the 2018 list contained data science jobs with more generic titles, 2019’s list suggests that companies are seeking out data science teams with different experience levels and skillsets.