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Sr Scientist - Large Molecule Ontology Specialist

Amgen

Sr Scientist - Large Molecule Ontology Specialist

full-timePosted: Jul 29, 2026Updated: Aug 28, 2026India - Hyderabad

Job Description

Career CategoryResearchJob DescriptionHOW MIGHT YOU DEFY IMAGINATION?If you feel like you’re part of something bigger, it’s because you are. At Amgen, our shared mission—to serve patients—drives all that we do. It is key to our becoming one of the world’s leading biotechnology companies. We are global collaborators who achieve together—researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It’s time for a career you can be proud of.Large Molecule Ontology Specialist (Large Molecule Discovery Informatics)LiveWhat you will doLet’s do this. Let’s change the world. In this vital and exciting role, you will serve as a Large Molecule Ontology Specialist within the Research organization, driving the development and implementation of ontology, metadata, and semantic data frameworks that enable scalable AI, advanced analytics, and cross-functional scientific collaboration.You will be responsible for defining and implementing assay and metadata standards across Large Molecule Discovery (LMD), ensuring semantic consistency and interoperability across experimental platforms, scientific workflows, and data modalities. The successful candidate will partner closely with research scientists, informaticians, data engineers, and enterprise data governance teams to establish harmonized ontologies, metadata frameworks, and FAIR data practices that improve data discoverability, reuse, and AI readiness.Operating at the intersection of biology, data science, and informatics, you will combine scientific domain expertise with a deep understanding of semantic technologies, ontology management, and scientific data standards to build foundational capabilities that accelerate discovery.In this role, your core responsibilities include:Develop and maintain LMD ontology frameworks, semantic standards, and controlled vocabularies across key discovery workflows and datasetsAlign ontologies with enterprise data standards and relevant external scientific ontologiesManage ontology lifecycle processes, including governance, versioning, change control, and stakeholder engagementDefine metadata models and requirements that improve data consistency, traceability, quality, and reuseAdvance FAIR data practices by establishing maturity metrics, monitoring KPIs, and embedding reusable data practices into research workflowsPartner with AI/ML, data engineering, and scientific teams to structure interoperable data assets for analytics, model training, and discoveryCollaborate with data product owners, data engineers, platform teams, and scientists to embed FAIR data practices into research workflows and data productsServe as a subject matter expert for semantic technologies, scientific data standards, stakeholder alignment, and ontology-enabled discovery capabilitiesWinWhat we expect of youWe are all different, yet we all use our unique contributions to serve patients. The dynamic professional we seek is a subject matter expert with these qualifications.Basic Qualifications:Doctorate degree with 7+ in Bioinformatics, Computational Biology, Data Science, Information Science, Life Sciences, Computer Science, or a related field and relevant industry experienceMaster’s degree with 8+ years of relevant experience, ORBachelor’s degree with 10+ years of relevant experiencePreferred Qualifications:Experience developing biomedical or scientific ontologies and applying semantic technologies, ontology design principles, and metadata management practicesProficiency with ontology and data standards tools and frameworks such as OWL, RDF, SKOS, Protégé, FAIR principles, and life science data standardsExperience integrating structured and unstructured scientific data across domains using data models, metadata architecture, and knowledge graph conceptsFamiliarity with AI/ML data requirements, scientific data engineering practices, large-scale data quality monitoring, Python, and SQLStrong ability to influence across matrixed organizations, facilitate stakeholder alignment, and communicate effectively in writing and verballyExperience leading cross-functional standards-development initiatives and working in SAFe/Agile environmentsThriveWhat you can expect of usAs we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being.Apply nowfor a career that defies imaginationObjects in your future are closer than they appear. Join us.careers.amgen.comApplication deadlineAmgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation..

Locations

  • India - Hyderabad

Skills Required

  • ontologyintermediate
  • AI/ML data requirementsintermediate

Required Qualifications

  • Doctorate degree with 7+ in Bioinformatics, Computational Biology, Data Science, Information Science, Life Sciences, Computer Science, or a related field and relevant industry experience (experience)
  • Master’s degree with 8+ years of relevant experience, OR (experience, 8 years)
  • Bachelor’s degree with 10+ years of relevant experience (experience, 10 years)

Preferred Qualifications

  • Experience developing biomedical or scientific ontologies and applying semantic technologies, ontology design principles, and metadata management practices (experience)
  • Proficiency with ontology and data standards tools and frameworks such as OWL, RDF, SKOS, Protégé, FAIR principles, and life science data standards (experience)
  • Experience integrating structured and unstructured scientific data across domains using data models, metadata architecture, and knowledge graph concepts (experience)
  • Familiarity with AI/ML data requirements, scientific data engineering practices, large-scale data quality monitoring, Python, and SQL (experience)
  • Strong ability to influence across matrixed organizations, facilitate stakeholder alignment, and communicate effectively in writing and verbally (experience)
  • Experience leading cross-functional standards-development initiatives and working in SAFe/Agile environments (experience)

Responsibilities

  • Let’s do this. Let’s change the world. In this vital and exciting role, you will serve as a Large Molecule Ontology Specialist within the Research organization, driving the development and implementation of ontology, metadata, and semantic data frameworks that enable scalable AI, advanced analytics, and cross-functional scientific collaboration.
  • You will be responsible for defining and implementing assay and metadata standards across Large Molecule Discovery (LMD), ensuring semantic consistency and interoperability across experimental platforms, scientific workflows, and data modalities. The successful candidate will partner closely with research scientists, informaticians, data engineers, and enterprise data governance teams to establish harmonized ontologies, metadata frameworks, and FAIR data practices that improve data discoverability, reuse, and AI readiness.
  • Operating at the intersection of biology, data science, and informatics, you will combine scientific domain expertise with a deep understanding of semantic technologies, ontology management, and scientific data standards to build foundational capabilities that accelerate discovery.
  • Develop and maintain LMD ontology frameworks, semantic standards, and controlled vocabularies across key discovery workflows and datasets
  • Align ontologies with enterprise data standards and relevant external scientific ontologies
  • Manage ontology lifecycle processes, including governance, versioning, change control, and stakeholder engagement
  • Define metadata models and requirements that improve data consistency, traceability, quality, and reuse
  • Advance FAIR data practices by establishing maturity metrics, monitoring KPIs, and embedding reusable data practices into research workflows
  • Partner with AI/ML, data engineering, and scientific teams to structure interoperable data assets for analytics, model training, and discovery
  • Collaborate with data product owners, data engineers, platform teams, and scientists to embed FAIR data practices into research workflows and data products
  • Serve as a subject matter expert for semantic technologies, scientific data standards, stakeholder alignment, and ontology-enabled discovery capabilities

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