Also called: Ontology Engineer, Semantic Data Engineer, Knowledge Engineer
Builds maps of facts and how they connect, such as drugs, genes and diseases, so search engines and AI systems can look things up and reason.
You design how 'customer', 'order' and 'product' link together, then write code to load millions of records into a graph database. Later you help an AI team connect their chatbot to the graph so it answers with real facts.
Estimate anchored on BLS database architects; tech and pharma pay the most.
Approximate: anchored on Bureau of Labor Statistics data for a broader job group.
Bachelor's degree (4-year), about 4 years after high school. Bachelor's in computer science, information science or a related field; some come from library science or linguistics.
Ways in: 4-year college, Graduate school. Training cost: $15k – $60k.
Majors to look at: Computer Science, Information Science, Library and Information Science, Data Science.
Growing about average. Companies use knowledge graphs to make AI answers more accurate, which has renewed demand.
Medium risk for 10 years. AI pulls facts out of text automatically; designing the structure, fixing errors and deciding what counts as true stay human.
Classes: AP Computer Science A, Logic or philosophy, AP Statistics.
Official data: O*NET occupation 15-1243.
Career Universe is an early version. Pay, training and AI-risk figures are estimates to start your own research, not verified facts. The research was written with AI research assistants, checked by validation scripts and spot-checked by hand. Check anything important with schools, employers and official sources. How the numbers work.