Senior Biomedical Ontologist

Hone is an online medical clinic at the forefront of transforming healthcare and enhancing longevity. We use cutting-edge scientific advancements to empower men and women to take control of their health and unlock their full potential. Our people are the heart of everything we do and drive our success. We approach every project through our brand values:

• Fight for the Customer
• Execute Ruthlessly
• Communicate Candidly, Clearly, and Kindly
• Collaborate Selflessly
• Practice Calculated Risk-Taking
• Maximize Joy and Gratitude

Hone has been fully virtual from day one and will continue to be a remote-first employer.

Our ideal candidate is a mission-driven, motivated multi-tasker who is invested in work that is fulfilling and impactful. They embrace change and tackle challenges with enthusiasm. They have an “all-in” disposition towards work, understanding that we are a fast-paced, high-growth organization with evolving priorities. They can excel at both independent tasks and collaborative work, leading with clear and candid communication. They exhibit humble leadership—the ability to drive initiatives forward while remaining excited about continuous learning and development opportunities. They feel strongly about being part of a team that advocates for people to live longer and better lives.

Hone is seeking a Senior Biomedical Ontologist to lead the development of our biomedical ontology and knowledge graph infrastructure in support of personalized health and longevity. Reporting to the Sr. Director of Data, Analytics, and Machine Learning, you will design and extend semantic frameworks that power clinical decision support and personalized treatment recommendations.

You’ll serve as our internal expert in biomedical ontologies, collaborating with clinical, data science, and product teams to represent complex relationships between aging biomarkers, therapeutic interventions, and health outcomes. This is a foundational role focused on building the semantic backbone that connects diverse biomedical data to real-world clinical insights.

Key responsibilities for this role include (but are not limited to) the following:

• →Design and maintain biomedical ontologies focused on longevity, aging biomarkers, and therapeutic interventions using OWL, RDF, and related standards
• →Ensure alignment with established biomedical vocabularies and standards (e.g., SNOMED CT, LOINC, Gene Ontology)
• →Collaborate with clinical experts to translate complex medical knowledge into structured, formal ontological representations
• →Partner with data engineering teams to define requirements for ETL processes that populate the knowledge graph from structured and unstructured sources. This is a hands-on role where you will be contributing to ETL building as well.
• →Specify and validate APIs and reasoning capabilities (e.g., SPARQL, GraphQL, semantic inference) to support clinical insights and knowledge-driven applications
  (Note: API development is led by platform engineers)
• →Collaborate with machine learning teams to expose ontological structures that support feature engineering, interpretability, and clinical modeling
• →Utilize agentic AI to automate standardization and maximize efficiency.
• →Establish ontology governance processes, including version control, change management, and quality assurance procedures
• →Mentor team members and contribute to internal education around semantic web technologies and biomedical informatics best practices
• →Stay current with advances in longevity science and integrate emerging concepts into the ontology framework when appropriate
• →Communicate ontology updates and graph insights clearly to both technical and clinical stakeholders across the organization

• 5+ years of experience in bioinformatics, computational biology, or biomedical informatics
• Advanced degree (MS or PhD) in Bioinformatics, Computational Biology, Computer Science, or a related field
• Experience with Gremlin/Cypher and graph databases such as Azure Cosmos DB/Neo4j
• Expertise in ontology engineering and semantic web technologies (e.g., OWL, RDF, RDFS, SPARQL)
• Hands-on experience developing and maintaining biomedical knowledge graphs or ontologies
• Proficiency in Python and SQL for data manipulation and integration tasks
• Familiarity with standard biomedical ontologies and terminologies (e.g., SNOMED CT, UMLS, Gene Ontology, LOINC, HPO)
• Experience with natural language processing (NLP) for biomedical text mining or knowledge extraction
• Familiarity with HIPAA compliance and healthcare data governance best practices
• Strong communication skills, with the ability to translate complex biomedical concepts for both technical and clinical audiences
• Experience working with clinical or biological data in a healthcare or research setting
• Experience working in agile, cross-functional teams
• Ability to multitask, prioritize, and adhere to deadlines while maintaining attention to detail and quality
• Comfortable in a fast-paced, frequently changing environment 
• Creative problem-solving skills with a results-driven mindset
• Can quickly learn new technology systems and communication tools
• Ability to work autonomously and collaboratively

• Knowledge of ontology development tools (e.g., Protégé, TopBraid)
• Exposure to cloud platforms (e.g., Azure, AWS, or GCP) and distributed data environments
• Understanding of molecular biology, aging mechanisms, and clinical research methodologies
• Experience with longevity research, aging biomarkers, or personalized/precision medicine
• Knowledge of graph machine learning, embeddings, or knowledge-guided feature engineering
• Mentorship experience and interest in supporting the growth of junior team members