Sr Scientist - Large Molecule Ontology Specialist

Amgen Technology; Hyderabad; On-site; INR 400,000 - 700,000; Full time

Job summary

Amgen Technology in Hyderabad, India invites a Large Molecule Ontology Specialist to drive ontology, metadata, and semantic data frameworks enabling scalable AI and cross-functional collaboration.

You will define metadata models, align ontologies with enterprise standards, and advance FAIR data practices across discovery workflows in LMD, partnering with scientists, data engineers, and governance teams.

Qualifications

• Doctorate with 7+ years in relevant biosciences or data science fields.
• Masters with 8+ years of relevant experience, or Bachelor with 10+ years.
• Experience developing biomedical ontologies and applying semantic technologies.
• Familiarity with data standards and governance practices.

Responsibilities

• Develop and maintain LMD ontology frameworks and semantic standards.
• Align ontologies with enterprise data standards and external ontologies.
• Manage ontology lifecycle, governance, and change control.
• Define metadata models to improve data consistency and reuse.
• Advance FAIR data practices within research workflows.
• Collaborate with AI/ML and data teams to structure interoperable data assets.
• Engage with data product owners and scientists to embed FAIR practices.
• Act as SME for semantic technologies and ontology-enabled discovery.

Skills

Ontology management

Semantic technologies

Data governance

AI/ML data readiness

Education

Doctorate in Bioinformatics/related field

Masters in related field

Bachelor in related field with experience

Tools

OWL

RDF

SKOS

Protégé

Job description

Job Summary

Lets do this. Lets 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.

Responsibilities

• 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

Requirements

We 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 experience
• Masters degree with 8+ years of relevant experience, OR
• Bachelors degree with 10+ years of relevant experience

Preferred Qualifications:

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