Principal Scientist, Data Science (Data Products, Integration & Analysis)
Johnson & Johnson
August 13, 2026
Remote friendly (Spring House, PA)
United States
IT
Position Summary
- Lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development.
- Create scalable, interoperable, AI-ready data products connecting discovery, preclinical, clinical, safety, and real-world evidence; enable validated-biomarker data assets.
- Establish data architecture, integration strategy, metadata framework, and productization approach for semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI.
- Build AI reasoning models to support translational safety decision making.
Key Responsibilities
- Define and execute a scientific data product strategy across discovery, translational science, preclinical safety, clinical development, pharmacovigilance, and real-world evidence.
- Design data integration frameworks and harmonization strategies (SEND, SDTM, ADaM, MedDRA, Imaging, Omics, Biomarker, Pathology, Real-world data).
- Lead AWS deployment strategy; partner for scalable pipelines/services.
- Lead development of curated datasets, semantic-ready products, feature stores, metadata products, scientific data services, AI-ready assets.
- Define metadata/quality standards; implement lineage/provenance/traceability and FAIR; monitor quality.
- Build predictive AIML models for translational safety.
Required Qualifications
- Master’s or PhD in CS, Data Engineering, Bioinformatics, Biomedical Informatics, Information Systems, Computational Biology, or related.
- 5+ years in scientific data engineering/architecture/products/life sciences informatics.
- Enterprise-scale scientific data products; experience in drug discovery/development, clinical research, or pharmacovigilance.
Technical/Preferred
- Expertise: data architecture, modeling, product design, cloud-native platforms, metadata management, governance, predictive modeling.
- AWS; data lakes/lakehouses; distributed processing; APIs/services; cataloging/lineage.
- Familiarity: SEND/SDTM/ADaM/MedDRA; preferred FHIR/OMOP/DICOM/biomarker & omics standards.
- Preferred: knowledge graphs/semantic architectures/GraphRAG; AI-ready data products/feature stores; ontology-driven integration; regulated environments.
Preferred Skills
- Advanced Analytics, Critical Thinking, Data Analysis, Data Quality, Data Visualization, Strategic Thinking, Technical Credibility, Process Improvements, Workflow Analysis (plus data privacy standards/reporting/coaching).
Base Pay Range
- $117,000.00 - $201,250.00
Benefits (time off)
- Vacation 120 hrs/yr; Sick 40 hrs/yr (CO:48, WA:56); Holidays 13 days/yr; Work/Personal/Family up to 40 hrs/yr; Parental leave 480 hrs; Bereavement 240 hrs (immediate) / 40 hrs (extended); Caregiver 80 hrs (52-week rolling); Volunteer 32 hrs/yr; Military Spouse Time-Off 80 hrs/yr.
- Lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development.
- Create scalable, interoperable, AI-ready data products connecting discovery, preclinical, clinical, safety, and real-world evidence; enable validated-biomarker data assets.
- Establish data architecture, integration strategy, metadata framework, and productization approach for semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI.
- Build AI reasoning models to support translational safety decision making.
Key Responsibilities
- Define and execute a scientific data product strategy across discovery, translational science, preclinical safety, clinical development, pharmacovigilance, and real-world evidence.
- Design data integration frameworks and harmonization strategies (SEND, SDTM, ADaM, MedDRA, Imaging, Omics, Biomarker, Pathology, Real-world data).
- Lead AWS deployment strategy; partner for scalable pipelines/services.
- Lead development of curated datasets, semantic-ready products, feature stores, metadata products, scientific data services, AI-ready assets.
- Define metadata/quality standards; implement lineage/provenance/traceability and FAIR; monitor quality.
- Build predictive AIML models for translational safety.
Required Qualifications
- Master’s or PhD in CS, Data Engineering, Bioinformatics, Biomedical Informatics, Information Systems, Computational Biology, or related.
- 5+ years in scientific data engineering/architecture/products/life sciences informatics.
- Enterprise-scale scientific data products; experience in drug discovery/development, clinical research, or pharmacovigilance.
Technical/Preferred
- Expertise: data architecture, modeling, product design, cloud-native platforms, metadata management, governance, predictive modeling.
- AWS; data lakes/lakehouses; distributed processing; APIs/services; cataloging/lineage.
- Familiarity: SEND/SDTM/ADaM/MedDRA; preferred FHIR/OMOP/DICOM/biomarker & omics standards.
- Preferred: knowledge graphs/semantic architectures/GraphRAG; AI-ready data products/feature stores; ontology-driven integration; regulated environments.
Preferred Skills
- Advanced Analytics, Critical Thinking, Data Analysis, Data Quality, Data Visualization, Strategic Thinking, Technical Credibility, Process Improvements, Workflow Analysis (plus data privacy standards/reporting/coaching).
Base Pay Range
- $117,000.00 - $201,250.00
Benefits (time off)
- Vacation 120 hrs/yr; Sick 40 hrs/yr (CO:48, WA:56); Holidays 13 days/yr; Work/Personal/Family up to 40 hrs/yr; Parental leave 480 hrs; Bereavement 240 hrs (immediate) / 40 hrs (extended); Caregiver 80 hrs (52-week rolling); Volunteer 32 hrs/yr; Military Spouse Time-Off 80 hrs/yr.