Principal Data Scientist - Oncology

What you'll do

• Design and implement a scalable knowledge graph infrastructure for data standardization in Oncology R&D.
• Apply graph-based data modeling to organize, integrate, and retrieve Oncology R&D data efficiently.
• Curate and extend ontologies using RDF standards to ensure clear mapping into established biomedical ontologies.
• Develop ingestion and curation pipelines to normalize and map concepts across diverse data sources.
• Draft documentation such as data dictionaries and flow diagrams to facilitate understanding of the knowledge graph.
• Partner with cross-functional teams to enable NLP/RAG over graphs for predictive modeling and terminology services.

What we're looking for

• Ph.D. or Master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or related fields.
• 5+ years of professional experience in health informatics and semantic technologies for biomedical applications.
• Experience in large-scale knowledge graph construction and ontology development in pharmaceutical or healthcare domains.
• Proficiency in semantic web technologies (SPARQL, RDF, OWL) and familiarity with graph databases (Neo4j, Amazon Neptune).
• Programming background in parser combinators, natural language processing, and linked data.
• Demonstrated work with complex biomedical datasets including clinical, genomics, and proteomics data.