Principal Scientist, Data Science (Data Products, Integration & Analysis)

Johnson & Johnson Innovative Medicine•Horsham, PA

6d•$117,000 - $201,250•Hybrid

About The Position

The Principal Scientific Data Scientist will lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development. This individual will be responsible for creating scalable, interoperable, and AI-ready data products that connect discovery, preclinical, clinical, safety, and real-world evidence domains, and enable the creation of validated-biomarker data assets. The role will 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. Working closely with scientific stakeholders, knowledge architects, AI engineers, and Amazon BioDiscovery platform teams, this individual will 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.

Requirements

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
Strategic thinker capable of defining long-term data product roadmaps.
Strong communicator who can bridge scientific and technical communities.
Ability to influence cross-functional teams without direct authority.
Strong execution focus with a bias toward scalable, reusable solutions.
Passion for transforming biomedical R&D through data, AI, and modern engineering practices.

Nice To Haves

Preferred familiarity with: FHIR, OMOP, DICOM, Biomarker and omics data standards
Experience supporting knowledge graphs, semantic architectures, or GraphRAG initiatives.
Experience building AI-ready data products and feature stores.
Familiarity with ontology-driven data integration approaches.
Experience partnering with cloud providers or external platform teams.
Experience operating in highly regulated scientific environments.

Responsibilities

Define and execute a scientific data product strategy supporting: Discovery Research, Translational Science, Preclinical Safety, Clinical Development, Pharmacovigilance, Real-World Evidence
Establish reusable, scalable data products that support analytics, AI, knowledge graph, and scientific reasoning use cases.
Develop product roadmaps aligned with organizational priorities and scientific objectives.
Design integration frameworks connecting heterogeneous scientific data sources.
Define data harmonization strategies spanning: SEND, SDTM, ADaM, MedDRA, Imaging, Omics, Biomarker, Pathology, Real-world data
Create architecture patterns supporting cross-domain data interoperability.
Define the implementation strategy for scientific data products deployed on AWS
Partner with Amazon engineering and deployed platform resources to deliver scalable data pipelines and data products.
Provide technical leadership and architectural oversight for implementation activities aligned recommendations from the Data Strategy group.
Ensure digital solutions align with enterprise architecture, security, governance, and AI-readiness requirements.
Lead design and implementation of: Curated datasets, Semantic-ready data products, Feature stores, Metadata products, Scientific data services, AI-ready data assets
Establish reusable patterns for data onboarding, transformation, validation, and publication.
Define metadata standards and data quality frameworks.
Implement lineage, provenance, traceability, and FAIR data principles.
Establish monitoring and quality controls for scientific data products.
Build predictive AIML models to support translational safety decision making.
Partner with: Discovery Scientists, Toxicologists, Clinical Scientists, Safety Scientists, Data Scientists and Data Strategy business partners, Knowledge Architects, AI Engineers
Translate scientific questions into scalable data products and technical solutions.

Benefits

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
Eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
Eligible to participate in the Company’s long-term incentive program.