Principal Data Scientist - R&D DSDH - Preclinical Sciences & Translational Safety (PSTS)

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, La Jolla, California, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

Johnson & Johnson Innovative Medicine is recruiting for Principal Data Scientist - R&D DSDH - Preclinical Sciences & Translational Safety (PSTS)

The primary location for this position is open to Spring House, PA; Titusville, NJ; Spring House, PA; Cambridge, MA; San Diego, CA; Beerse, Belgium; Madrid, Spain; or Barcelona, Spain.

Candidate Interested in our Europe based locations, please apply to: R-069190

Position Summary

The R&D Data Science organization is seeking a Data Scientist to leverage advanced machine learning, robust data engineering techniques, and domain expertise to drive impactful decisions and generate actionable insights within the Pharmaceutical Sciences & Translational Safety (PSTS) organization. In this role, you will work closely with multidisciplinary teams-including toxicologists, PK/PD specialists, in vivo researchers, and safety professionals-to create AI-ready datasets, develop predictive models, and deliver analytical solutions that promote improved safety evaluations and facilitate translational research.

The successful candidate possesses hands-on experience in machine learning and data engineering, complemented by a solid understanding of toxicology, pharmacokinetics/pharmacodynamics (PK/PD), in vivo experimentation, and translational science. Additionally, this role requires strong communication and problem-solving skills, a passion for innovation, and the ability to adapt to evolving scientific challenges in pharmaceutical R&D.

Key Responsibilities

Machine Learning & Modeling

• Develop and deploy ML/AI models to support safety signal detection, dose selection, PK/PD modeling, toxicology insights, and translational interpretation.
• Implement representation-learning, predictive modeling, and multivariate analytics for datasets spanning in vivo studies, in vitro assays, exposure-response data, and pathology information.
• Partner with scientific SMEs to design modeling strategies aligned with PSTS decision points.
• Apply model governance, versioning, and validation standards consistent with R&D AI practices.

Data Engineering & Pipeline Development

• Build and maintain scalable data pipelines that integrate PSTS-relevant data sources (e.g., toxicology studies, PK/PD datasets, biomarker readouts, animal study repositories).
• Transform raw experimental outputs into standardized, analysis-ready, AI-ready datasets using Python, R, and cloud-native services.
• Contribute to harmonized scientific data models in collaboration with data engineering and ontology teams.

Scientific Domain Integration

• Work directly with toxicology, DMPK, and safety stakeholders to interpret scientific context and translate study designs into computational requirements.
• Apply understanding of mechanism-based toxicology, exposure-response concepts, and in vivo study structures to guide data transformations and modeling strategies.
• Enhance cross-study comparability via standardized terminologies, metadata practices, and quality checks.
• Collaborate with PSTS functional experts, R&D Data Science teams, and platform architects to ensure high-quality, scalable data solutions.

Qualifications

Required

• Advanced degree (MS or PhD) in Data Science, Computational Biology, Toxicology, Pharmacology, Biomedical Engineering, Computer Science, or related field.
• 3+ years of experience applying machine learning and/or data engineering to scientific or biomedical datasets.
• Proficiency with Python and/or R, SQL, and modern data engineering tooling (cloud computing, workflow orchestration, version control).
• Experience with ML model development, evaluation, and deployment pipelines.
• Experience working with biological, toxicology, PK/PD, or in vivo datasets.

Preferred

• Experience in safety sciences, ADME/DMPK, toxicogenomics, or biomarker analytics.
• Familiarity with scientific data formats (e.g., assay outputs, histopathology data, PK time-course datasets).
• Exposure to ontologies, semantic technologies, or knowledge graph integration for scientific domains.
• Experience with cloud-based data architectures (AWS S3, Snowflake, Redshift).
• Understanding of regulatory data standards (e.g., SEND, CDISC).

Why This Role Is Unique

This is a rare opportunity to grow in one of the world's most ambitious and fastest-growing R&D Data Science organizations, shaping how PSTS data powers next-generation therapies in the largest biomedical company on the planet. Your work will directly accelerate Johnson & Johnson's scientific discovery, fuel AI innovation, and impact patients globally.

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Required Skills: