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

Johnson & Johnson Innovative Medicine•Horsham, PA

18d•$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 that support AI-enabled drug discovery and development. The role creates scalable, interoperable, AI-ready data products connecting discovery, preclinical, clinical, safety, and real-world evidence domains, including validated-biomarker data assets. It establishes the data architecture, integration strategy, metadata framework, and productization approach for semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI applications. The position also builds AI reasoning models and predictive machine-learning models to support data-driven translational safety decision making. Working with scientific stakeholders, knowledge architects, AI engineers, and Amazon BioDiscovery platform teams, the role defines the future-state scientific data ecosystem and delivers high-quality data products for translational science and patient safety initiatives. It develops and operationalizes products that enable integration, harmonization, and reuse of data across the drug discovery and development lifecycle, and provides technical and architectural leadership for solutions deployed on AWS. The position is based at one of the listed Johnson & Johnson locations in Pennsylvania or New Jersey. It is marked hybrid. The anticipated base pay range is $117,000 to $201,250. Eligible employees may participate in the company retirement and savings plans, long-term incentive program, and specified paid time-off and leave benefits.

Requirements

Master’s or PhD in Computer Science, Data Engineering, Bioinformatics, Biomedical Informatics, Information Systems, Computational Biology, or a related scientific discipline.
At least 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, and predictive model development.
Experience with AWS-based data platforms, data lakes and lakehouses, distributed data processing, APIs and data services, and data cataloging and lineage solutions.
Strong familiarity with SEND, SDTM, ADaM, and MedDRA.
Ability to communicate across scientific and technical communities and influence cross-functional teams without direct authority.
Strategic thinking, strong execution focus, and ability to develop long-term data product roadmaps and scalable, reusable solutions.

Nice To Haves

Familiarity with FHIR, OMOP, DICOM, and 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.
Passion for transforming biomedical R&D through data, AI, and modern engineering practices.

Responsibilities

Define and execute a scientific data product strategy supporting discovery research, translational science, preclinical safety, clinical development, pharmacovigilance, and real-world evidence.
Establish reusable, scalable data products for analytics, AI, knowledge graphs, and scientific reasoning use cases.
Develop product roadmaps aligned with organizational priorities and scientific objectives.
Design integration frameworks connecting heterogeneous scientific data sources and define cross-domain data harmonization and interoperability patterns.
Define the implementation strategy for scientific data products deployed on AWS and partner with Amazon engineering and platform resources to deliver scalable data pipelines and products.
Provide technical leadership and architectural oversight for implementation activities, aligned with recommendations from the Data Strategy group.
Ensure digital solutions align with enterprise architecture, security, governance, and AI-readiness requirements.
Lead the design and implementation of curated datasets, semantic-ready data products, feature stores, metadata products, scientific data services, and AI-ready data assets in collaboration with the Data Strategy group.
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; and establish monitoring and quality controls.
Build predictive AI/ML models to support translational safety decision making.
Partner with discovery scientists, toxicologists, clinical scientists, safety scientists, data scientists, Data Strategy business partners, knowledge architects, and AI engineers.
Translate scientific questions into scalable data products and technical solutions.

Benefits

Company consolidated retirement plan (pension) and savings plan (401(k)), subject to plan terms.
Eligibility to participate in the company long-term incentive program.
Vacation: 120 hours per calendar year, subject to policy and hire-date terms.
Sick time: 40 hours per calendar year, with specified higher amounts for employees residing in Colorado or Washington.
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, or foster care of a child.
Bereavement leave: up to 240 hours for an immediate family member and 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.