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Senior Scientific Knowledge Engineer

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GSK

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Location:
United States , Cambridge, Massachusetts ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

145200.00 - 242000.00 USD / Year
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Job Description:

The Onyx Research Data Tech organization is GSK’s Research data ecosystem which has the capability to bring together, analyze, and power the exploration of data at scale. We partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. The goal is to ensure scientists have the right data and insights when they need it to give them a better starting point for and accelerate medical discovery. Ultimately, this helps us get ahead of disease in more predictive and powerful ways.

Job Responsibility:

  • Definition of schemas and data models of scientific information required for the creation of value adding data products
  • Accountable for the quality control (through validation and verification) of mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling
  • Working with Product managers/engineers confidently convert business need into defined deliverable business requirements to enable the integration of large-scale biology data
  • Collaborate with external groups to align GSK data standards with industry/ academic ontologies
  • Support effective ingestion of data by GSK through understanding the entry requirements required by platform engineering teams
  • Provides bespoke subject matter expertise for R&D data to translate deep science into data for actionable insights
  • Champion data lineage, data quality, and FAIR data principles across the Onyx platform
  • Contribute to and maintain documentation of data standards, ontology decisions, and mapping rationale
  • Support self-service data enablement by ensuring metadata and knowledge products are accessible, well-documented, and usable by scientists and analysts

Requirements:

  • Masters degree in Bioinformatics, Biomedical Science, Biomedical Engineering, Molecular Biology, or Computer Science (with a life science application focus)
  • 6+ years of relevant work experience
  • Experience contributing to Knowledge Graph development efforts, including entity modeling, relationship design, and schema governance
  • Experience in operating and leading across organizational boundaries a matrixed team
  • Experience with industry standard data management / metadata platforms e.g. Collibra, Datahub, Datum, Informatica
  • Proficiency in at least one programming language — preferably Python — for scripting vocabulary mappings, building data models, automating QC, and prototyping pipelines
  • Experience with bioinformatics pipelines and workflow management systems (e.g., Nextflow)

Nice to have:

  • Membership of industry committee, board, consortium, or data standards group
  • Participation in peer-reviewed research (both publication and review), particularly in genetics and/or bioinformatics
  • Experience with data governance and data quality tooling (e.g., Ataccama, Informatica, Talend, OpenRefine, Great Expectations, dbt)
  • Experience with industry standard tools for building data protocols e.g. Avro, Protocol Buffers, Thrift
  • Experience with at least one programming language – e.g. Python – for scripting vocabulary mappings, building data models, etc
  • Experience supporting LLM integration or AI-readiness workflows — including metadata enrichment, entity linking, embedding pipelines, or retrieval-augmented generation (RAG) architectures
  • Understanding of vector databases and their role in semantic search and knowledge retrieval (e.g., Weaviate, Chroma)
  • Familiarity with cloud data platforms and infrastructure relevant to large-scale biological data (e.g., AWS, GCP, Azure)
  • Familiarity with graph database technologies (e.g., Neo4j, Amazon Neptune, Stardog, GraphDB, TigerGraph)
  • Experience designing or contributing to FAIR data frameworks, data catalogs, or self-service data enablement initiatives
  • Hands-on experience with open-source ontology tools and languages: Protégé, SPARQL, OWL, SKOS, SHACL, RML, RDF/Turtle
  • Working knowledge of major life sciences ontologies: Gene Ontology (GO), OBO Foundry ontologies (CL, UBERON, HPO, MONDO, CHEBI, EFO, CLO), MeSH, SNOMED CT, UMLS
  • Experience with CDISC standards (SDTM, ADaM, SEND) or other clinical/research data standards relevant to pharmaceutical R&D
  • Familiarity with linked data principles and semantic web technologies
  • Experience with multi-omics data formats and standards (e.g., h5ad/AnnData, VCF, FASTQ, MAF, CellXGene, GEO)
  • Experience with industry-standard tools for building data serialization protocols (e.g., JSON Schema, LinkML)
What we offer:
  • Competitive base salary
  • Annual bonus based on company performance
  • Flexible working options available for most roles
  • Learning and career development
  • Access to healthcare & wellbeing programmes
  • Employee recognition programmes
  • Health care and other insurance benefits (for employee and family)
  • Retirement benefits
  • Paid holidays
  • Vacation
  • Paid caregiver/parental and medical leave
  • Eligibility to participate in our share based long term incentive program

Additional Information:

Job Posted:
March 27, 2026

Employment Type:
Fulltime
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