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Niche ontology specialization reduces applicant pool, but Tier-1 employer and metro location increase competition.
High: requires domain-specific life-science knowledge, ontology experience, and FAIR data practices not easily transferable.
High: explicit senior experience thresholds, advanced degrees, and specialized ontology and life-science tooling are required.
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Develop and maintain large molecule ontology frameworks, semantic standards, and controlled vocabularies across discovery workflows and datasets.
Define and implement assay and metadata standards to ensure semantic consistency and interoperability across experimental platforms, scientific workflows, and data modalities.
Partner cross-functionally with scientists, informaticians, data engineers, and governance teams to establish FAIR data practices and enable AI readiness and advanced analytics.
Doctorate degree with 7+ years in Bioinformatics, Computational Biology, Data Science, Information Science, Life Sciences, Computer Science or related field with relevant industry experience; OR Master’s with 8+ years; OR Bachelor’s with 10+ years relevant experience.
Experience developing biomedical or scientific ontologies and applying semantic technologies and metadata management practices.
Proficiency with ontology and data standards tools such as OWL, RDF, SKOS, Protégé, and FAIR principles.
Work Experience Required: Minimum 7 years with Doctorate, or equivalent as per education; Notice period: Not explicitly mentioned in the JD.
Deep expertise at the intersection of biology, data science, and informatics with strong knowledge of semantic technologies and ontology management.
Proven ability to influence and align stakeholders across matrixed organizations and lead cross-functional standards-development initiatives.
Experience working with AI/ML data requirements, scientific data engineering, and in SAFe/Agile environments.