Principal Scientist, Data Science – Data Products, Integration & Analysis

Johnson & Johnson

Principal Scientist leading design and implementation of AI-ready scientific data products. Collaborating with stakeholders to enhance drug discovery and development processes at Johnson & Johnson.

Posted 7/17/2026full-timeCambridge • Massachusetts, New Jersey, Pennsylvania • 🇺🇸 United StatesLead💰 $117,000 - $201,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in designing and implementing scientific data products and integration strategies for AI-enabled drug discovery, with a strong focus on data architecture, metadata management, and predictive model development. Proven ability to deliver high-quality, interoperable data solutions that support translational science and patient safety initiatives.

Highest-signal resume keywords

Data ArchitectureData Product DesignPredictive Model DevelopmentAWS-Based Data PlatformsScientific Data Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingData GovernanceCloud-Native Data PlatformsMetadata ManagementData IntegrationData HarmonizationSemantic ReasoningGraphRAGAdvanced AnalyticsFeature Store Development

Tools & Technologies

Data LakesLakehousesAPIsData Cataloging SolutionsLineage Solutions

Industry Keywords

SENDSDTMADaMMedDRAPharmacovigilanceTranslational ScienceReal-World EvidenceDrug DiscoveryClinical DevelopmentOmics Data Standards

Tech Stack

Tools & technologies

AWSCloud

About the role

Key responsibilities & impact

Lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development.
Create scalable, interoperable, and AI-ready data products that connect discovery, preclinical, clinical, safety, and real-world evidence domains.
Establish the data architecture, integration strategy, metadata framework, and productization approach needed to support semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI applications.
Define the future-state scientific data ecosystem and ensure high-quality data products are delivered to support translational science and patient safety initiatives.
Build AI reasoning models to support data-driven translational safety decision making.
Define and execute a scientific data product strategy supporting Discovery Research, Translational Science, Preclinical Safety, Clinical Development, Pharmacovigilance, Real-World Evidence.
Design integration frameworks connecting heterogeneous scientific data sources and define data harmonization strategies spanning SEND, SDTM, ADaM, MedDRA, Imaging, Omics, Biomarker, Pathology, Real-world data.
Lead design and implementation of curated datasets, semantic-ready data products, feature stores, metadata products, scientific data services, and AI-ready data assets.
Define metadata standards and data quality frameworks, implement lineage, provenance, traceability, and FAIR data principles.

Requirements

What you’ll need

Master’s or PhD in: Computer Science, Data Engineering, Bioinformatics, Biomedical Informatics, Information Systems, Computational Biology, or Related scientific discipline
5+ years of experience in scientific data engineering, data architecture, data products, or life sciences informatics.
Demonstrated experience designing and delivering enterprise-scale scientific data products.
Experience supporting drug discovery, development, clinical research, or pharmacovigilance organizations.
Experience developing predictive models in drug discovery, development, clinical research, or pharmacovigilance organizations.
Strong expertise in: Data architecture, Data modeling, Data product design, Cloud-native data platforms, Metadata management, Data governance, Predictive model development
Experience with: AWS-based data platforms, Data lakes and lakehouses, Distributed data processing, APIs and data services, Data cataloging and lineage solutions
Strong familiarity with: SEND, SDTM, ADaM, MedDRA
Preferred familiarity with: FHIR, OMOP, DICOM, Biomarker and omics data standards

Benefits

Comp & perks

Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year