Super Data Science: ML & AI Podcast with Jon Krohn
Super Data Science: ML & AI Podcast with Jon Krohn

856: The Fastest-Growing Jobs Are AI Jobs

Get excited: The fastest-growing jobs in the US are AI Engineer and AI Consultant. In this Five-Minute Friday, Jon Krohn looks into the reports that reveal this job growth, and the trends any data scientist and AI professional will want to watch in 2025. Additional materials: www.superdatascience.co

Featured Speakers

Jon Krohn HostJohn Crohn Guest

Topics Discussed

Episode Summary

Executive Summary: John Crohn reviews listener feedback, then breaks down LinkedIn’s 2024 fastest-growing jobs analysis. He explains why job-growth measurement is hard, highlights AI engineer as the top U.S. role, AI consultant as #2, and AI researcher as #12, and shows that AI-related roles are rising globally while traditional data scientist titles are fragmenting into more specialized AI jobs.

Main Topics: Listener feedback and show positioning: The episode opens with shout-outs to recent reviews, reinforcing the show’s supportive, optimistic tone and its usefulness for career changers and technical listeners. Why measuring job growth is difficult: Crohn explains limitations of using job postings and title standardization, noting that job titles vary across companies and need bucketing into standardized categories for meaningful comparison. LinkedIn’s methodology for fastest-growing jobs: He summarizes LinkedIn Economic Graph Research’s approach: millions of jobs started by members between Jan 2022 and Jul 2024, with exclusions for low-significance or atypical roles. Fastest-growing jobs in the U.S.: AI engineer ranks first, AI consultant second, and AI researcher twelfth in the U.S., showing strong demand for AI-focused roles across technical and business-oriented tracks. Global spread of AI-related roles: Crohn notes that AI engineering and AI research also rank highly in multiple countries, indicating that the AI hiring boom is not limited to the U.S. Shift from data scientist to specialized AI roles: He argues that data scientist has ceded high-growth status to more AI-specific titles, reflecting specialization rather than disappearance of data science skills. Learning resources for aspiring AI engineers: The episode ends with recommendations for further learning via a prior podcast episode with Ed Donner and Chip Huyen’s book AI Engineering.

Key Arguments: Job growth analysis is tricky because job titles vary widely and posting data can be noisy, duplicated, or misleading. LinkedIn’s standardized, large-scale approach is more reliable than simple job-posting counts because it uses millions of member-started jobs and excludes low-quality edge cases. AI engineer is now the clearest fastest-growing role in the U.S., signaling strong demand for applied AI skills like LLMs, NLP, and PyTorch. AI consultant’s high ranking shows that the AI boom includes commercial, operational, and product-oriented roles, not just deeply technical ones. AI researcher’s appearance near the top demonstrates that advanced AI algorithm work is also growing rapidly, albeit with more in-office expectations. Data scientist is not disappearing; rather, its responsibilities are being redistributed into more specialized AI roles as the field matures. The growth of AI roles across countries suggests a broad international labor-market shift, not a niche U.S.-only trend.

Data Points: Fastest-growing job in the U.S.: AI engineer - LinkedIn’s 2024 U.S. growth rankings as discussed in the episode Second fastest-growing job in the U.S.: AI consultant - LinkedIn’s 2024 U.S. growth rankings 12th fastest-growing job in the U.S.: AI researcher - LinkedIn’s 2024 U.S. growth rankings Data period analyzed: January 2022 to July 2024 - LinkedIn Economic Graph Research team’s methodology Countries with LinkedIn reports mentioned: 20 countries - Australia, Brazil, Canada, France, Germany, India, Indonesia, Ireland, Israel, Italy, Mexico, Netherlands, Saudi Arabia, Spain, Sweden, Switzerland, Turkey, UAE, UK, US AI engineer top skills: LLMs, natural language processing, PyTorch - Skills listed in the U.S. AI engineer report summary Top cities for AI engineers: San Francisco, New York, Boston - U.S. AI engineer report summary Most common transitions into AI engineer: Full-stack engineer, research assistant, data scientist - LinkedIn transition data for AI engineer roles AI engineer remote work: 36% fully remote; 27% hybrid - U.S. AI engineer working-arrangement data AI researcher remote work: 11% fully remote; 19% hybrid - U.S. AI researcher working-arrangement data AI consultant top skill: Prompt engineering - Skill highlighted for AI consultant roles AI consultant common transition: Operations associate - Role transition into AI consultant AI researcher top skill: Deep learning - Skill highlighted for AI researcher roles AI engineer rank in the UK: #1 - Among fastest-growing roles in the UK AI engineer rank in the Netherlands: #1 - Among fastest-growing roles in the Netherlands AI engineer rank in Sweden: #5 - Among fastest-growing roles in Sweden AI engineer rank in Canada: #6 - Among fastest-growing roles in Canada AI engineer rank in Israel: #6 - Among fastest-growing roles in Israel AI engineer rank in India: #12 - Among fastest-growing roles in India AI researcher rank in Canada: #3 - Among fastest-growing roles in Canada AI researcher rank in Israel: #3 - Among fastest-growing roles in Israel AI researcher rank in the Netherlands: #9 - Among fastest-growing roles in the Netherlands

Pivotal Quotes: "the fastest-growing job in the U.S. is AI engineer" — John Crohn: Core takeaway introducing the main ranking result "AI consultant" — John Crohn: Second-fastest-growing U.S. role, emphasizing non-engineering AI career paths "data scientist has ceded its formerly high-growth position to these more AI-specific job titles" — John Crohn: Explains the labor-market shift from broad data science to specialized AI roles

Implications: AI is reshaping hiring across technical, research, and business functions. For job seekers, this favors targeted AI upskilling; for employers, it signals intensified competition for specialized talent and a broader redefinition of data science careers.

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