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Johnson & Johnson
Johnson & Johnson
H1B Visa SponsorHealthcareHealthcare InsurancePharmaceuticals
Johnson & Johnson is a global healthcare company working across innovative medicine and medical technology. Its teams develop solutions in oncology, immunology, neuroscience, specialty ophthalmology, interventional care, and orthopaedics, combining science and technology to address complex health needs. The company also emphasizes health equity, environmental sustainability, diversity, and inclusion as it serves providers, patients, and communities worldwide.
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Principal Scientist, Data Science – Data Products and Integration (Hybrid, Spring House)

Lead the development of AI-ready scientific data products and integration strategies for Johnson & Johnson’s drug discovery and development work. Support predictive modeling, knowledge graphs, and translational safety decisions.

USUnited StatesNJNew JerseyPAPennsylvania
$117,000 – $201,250 / year
HybridFull-timeLeadEnglish RequiredData Scientist
AWSCloud

Description

  • Lead the design and evolution of scientific data products and integration strategies for AI-enabled drug discovery and development.
  • Build scalable, interoperable, AI-ready data products spanning discovery, preclinical, clinical, safety, and real-world evidence.
  • Set data architecture, integration, metadata, and productization approaches for semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI.
  • Develop AI reasoning and predictive machine learning models to inform translational safety decisions.
  • Set and deliver data product strategies for discovery research, translational science, preclinical safety, clinical development, pharmacovigilance, and real-world evidence.
  • Create reusable data products, roadmaps, and scalable patterns for analytics, AI, knowledge graphs, and scientific reasoning.
  • Design integration and harmonization approaches for SEND, SDTM, ADaM, MedDRA, imaging, omics, biomarkers, pathology, and real-world data.
  • Define deployment strategies for scientific data products on AWS.
  • Work with Amazon engineering and platform teams to deliver scalable data pipelines and products.
  • Provide technical leadership and architectural oversight guided by Data Strategy recommendations.
  • Ensure digital solutions satisfy enterprise architecture, security, governance, and AI-readiness requirements.
  • Lead the creation of curated datasets, semantic-ready products, feature stores, metadata products, scientific data services, and AI-ready assets.
  • Set reusable methods for data onboarding, transformation, validation, and publication.
  • Define metadata standards and data quality frameworks.
  • Implement lineage, provenance, traceability, FAIR principles, monitoring, and quality controls.
  • Collaborate with discovery, toxicology, clinical, safety, and data scientists, as well as Data Strategy partners, knowledge architects, and AI engineers.
  • Turn scientific questions into scalable data products and technical solutions.

Requirements

  • Master’s or PhD in computer science, data engineering, bioinformatics, biomedical informatics, information systems, computational biology, or a related scientific field.
  • At least five years of experience in scientific data engineering, data architecture, data products, or life sciences informatics.
  • Experience designing and delivering scientific data products at enterprise scale.
  • Experience supporting drug discovery, development, clinical research, or pharmacovigilance organizations.
  • Experience developing predictive models for drug discovery, development, clinical research, or pharmacovigilance organizations.
  • Strong command of data architecture and modeling, data product design, cloud-native platforms, metadata management, data governance, and predictive model development.
  • Experience with AWS data platforms, data lakes and lakehouses, distributed processing, APIs and data services, and data cataloging and lineage tools.
  • Strong familiarity with SEND, SDTM, ADaM, and MedDRA.
  • Familiarity with FHIR, OMOP, DICOM, and biomarker and omics data standards is preferred.
  • Experience with knowledge graphs, semantic architectures, GraphRAG, AI-ready data products, feature stores, ontology-based integration, cloud providers or external platform teams, and regulated scientific settings is preferred.
  • Ability to define long-term data product roadmaps.
  • Ability to connect scientific and technical teams and influence cross-functional groups without direct authority.

Benefits

  • Retirement pension plan.
  • 401(k) savings plan.
  • Long-term incentive program.
  • 120 hours of vacation per calendar year.
  • 40 hours of sick time per calendar year; 48 hours for Colorado employees and 56 hours for Washington employees.
  • 13 paid holidays per calendar year, including floating holidays.
  • Up to 40 hours of Work, Personal and Family Time per calendar year.
  • 480 hours of parental leave within one year of a child’s birth, adoption, or foster placement.
  • Bereavement leave per calendar year: 240 hours for an immediate family member or 40 hours for an extended family member.
  • 80 hours of caregiver leave in a rolling 52-week period.
  • 32 hours of volunteer leave per calendar year.
  • 80 hours of military spouse time off per calendar year.
  • Inclusive interview accommodations for applicants with disabilities.

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