Biological Ontologist (Staff Scientist)

We are looking for an experienced Staff Scientist (Biological Ontologist) to join our growing Product & Science Team. You will be responsible for developing and managing ontologies to enhance data integration and support AI-driven drug discovery processes. This role will work with our innovative product, built on a knowledge graph of experimental evidence extracted from the corpus and a biological ontological knowledge base that acts as the semantic foundation for our proprietary data. We are seeking a candidate with subject matter expertise in biomedical data to continue evolving our proprietary biological ontological knowledge base.

You Will:

• Devise and implement the strategy for developing and maintaining BenchSci's proprietary biological ontology.
• Define the diverse biomedical data sources that will be integrated into our ontology, ensuring high-quality and comprehensive coverage.
• Work with Engineering to develop and deliver a data integration plan that guarantees interoperability and seamless integration of diverse biomedical data.
• Collaborate closely with engineering and product teams to maximise the impact of our ontology on product development.
• Collaborate with Engineering in defining the data strategy that ensures BenchSci’s ontology retains a high degree of connectivity enabling traversal and reasoning over our data by leveraging mid to high level ontologies and interoperability-enabling xref metadata.
• Advise Engineering colleagues on the evolution of our internal data model to ensure we minimise semantic lossiness when mapping entity types and predicates from third party ontologies to BenchSci’s proprietary ontology.
• Demonstrate strong leadership, making sound decisions in a fast-paced and evolving environment.
• Implement and oversee "quality by design" principles to maintain the accuracy, consistency, and completeness of BenchSci's ontological data.
• Create and maintain thorough documentation of our ontology, including definitions, relationships, and user guidelines.
• Provide training and support to internal teams on ontological principles, design, development and best practices.

You Have:

• A minimum of a Master’s degree in Bioinformatics, Biology, Computer Science, Information Science, or a related field. A Ph.D. is preferred.
• 7+ years of industry experience in ontology development and management, particularly in biotechnology or life sciences.
• Experience leveraging high and mid-level biological ontologies such as BioLink.
• Proficiency in ontology languages (e.g., OWL, RDF), ontology development tools (e.g., Protégé), ontology query language (SPARQL, cypher, SQL, GQL), and some familiarity with relevant programming languages (e.g., Python).
• Familiar with ontology reasoning tools, particularly in the biology domain (e.g. ELK, HermiT, and Pellet).
• Experience with applying these tools for tasks like classification and consistency checking in biomedical ontologies.
• A solid understanding of graph validation concepts, including SHACL (Shapes Constraint Language), to ensure data integrity and compliance within ontological frameworks.
• Strong understanding of biological concepts and terminologies and a deep understanding of biomedical ontologies (e.g., MONDO, MeSH, SNOMED CT).Deep understanding of the crucial role that ontologies play in providing a foundational semantic layer to knowledge graphs.
• Ability to analyse complex data and develop logical, ontological structures.
• High accuracy and attention to detail in managing and curating biological ontological data.
• Strong problem-solving abilities to address data integration and interoperability challenges.
• Excellent written and verbal communication skills to effectively document and convey complex ontological information.
• Strong interpersonal skills and the ability to work collaboratively within multidisciplinary teams.
• Deep industry knowledge and awareness of current trends and advancements in biotechnology and life sciences.
• Ability to adapt to evolving technologies and methodologies in ontology and biotechnology.