Senior AI Data Scientist / Knowledge Graph Engineer

What this role looks like

Automated interpretation based only on the supplied job description. This is not the original job description.

What the role is really about: The supplied brief points to a role primarily centred on hands-on engineering and build work. Alongside that, it places meaningful emphasis on documentation and knowledge transfer.

What you would actually be doing: In practical terms, the work described covers building and developing technical solutions, shaping technical designs and solution decisions, automating delivery and improving engineering/deployment workflows, and working with data pipelines, models or analytical outputs.

What this role expects from you as an applicant: The source explicitly asks for proven experience with graph retrieval, traversal and query design. The JD also looks for strong experience transforming complex technical, legal or regulatory documentation into Knowledge Graphs; strong understanding of AI evaluation, including extraction accuracy, precision/recall, groundedness and answer faithfulness; and experience with graph databases such as ArangoDB, Neo4j, Neptune or FalkorDB is highly. The role's Core Skills also point to application-development capability around Python; data capability across ETL; and additional core capability in Data Science and LLM.