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

At Johnson & Johnsonwe believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented treated and curedwhere treatments are smarter and less invasive andsolutions are our expertise in Innovative Medicine and MedTech we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow and profoundly impact health for more at

As guided by Our Credo Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge Massachusetts United States of America Horsham Pennsylvania United States of America Raritan New Jersey United States of America Spring House Pennsylvania United States of America Titusville New Jersey United States of America

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments finding cures and pioneering the path from lab to life while championing patients every step of the way.

Learn more at Summary

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.

Mission

Build and operationalize AI-ready scientific data products that enable seamless integration harmonization and reuse of data across the drug discovery and development lifecycle.

Key Responsibilities

Scientific Data Product Strategy

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.

Data Integration Architecture

• 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.

Digital Platform Leadership

• 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.

Data Product Development

• In collaboration with Data Strategy group 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.

Data Quality & Metadata

• Define metadata standards and data quality frameworks.

• Implement lineage provenance traceability and FAIR data principles.

• Establish monitoring and quality controls for scientific data products.

Data Analysis:

• Build predictive AIML models to support translational safety decision making.

Stakeholder Engagement

• 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.

Required Qualifications

Education

• Masters or PhD in:

  • Computer Science

  • Data Engineering

  • Bioinformatics

  • Biomedical Informatics

  • Information Systems

  • Computational Biology

  • Related scientific discipline

Experience

• 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.

Technical Expertise

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

Scientific Data Standards

Strong familiarity with:

• SEND

• SDTM

• ADaM

• MedDRA

Preferred familiarity with:

• FHIR

• OMOP

• DICOM

• Biomarker and omics data standards

Preferred Qualifications

• 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.

Leadership Competencies

• 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.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity age national origin disability protected veteran status or other characteristics protected by federal state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants needs. If you are an individual with a disability and would like to request an accommodation please email the Employee Health Support Center () or contact AskGS to be directed to your accommodation resource.

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Required Skills:

Preferred Skills:

Advanced Analytics Coaching Critical Thinking Data Analysis Data Privacy Standards Data Quality Data Reporting Data Savvy Data Science Data Visualization Digital Fluency Econometric Models Organizing Process Improvements Strategic Thinking Technical Credibility Workflow Analysis

The anticipated base pay range for this position is :

$117000.00 - $201250.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans employees are eligible to participate in the Companys consolidated retirement plan (pension) and savings plan (401(k)).

This position is eligible to participate in the Companys long-term incentive program.

Subject to the terms of their respective policies and date of hire employees are eligible for the following time off 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 period10 days

Volunteer Leave 32 hours per calendar year

Military Spouse Time-Off 80 hours per calendar year

For additional general information on Company benefits please go to: - Experience:

Staff IC