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

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 .

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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 toSpring House PA; Titusville NJ; Spring House PA; Cambridge MA; San Diego CA; Beerse Belgium; Madrid Spain; or Barcelona Spain.

Candidate Interested in our US based locations please apply to: R-067785

J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology immunology neuroscience cardiopulmonary and specialty ophthalmology. Our goal is to help people live longer healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market from patients to practitioners and from clinics to hospitals. To learn more about Johnson & Johnson Innovative Medicine visit 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) this role you will work closely with multidisciplinary teamsincluding toxicologists PK/PD specialists in vivo researchers and safety professionalsto 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 representationlearning predictive modeling and multivariate analytics for datasets spanning in vivo studies in vitro assays exposureresponse 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 PSTSrelevant data sources (e.g. toxicology studies PK/PD datasets biomarker readouts animal study repositories).
• Transform raw experimental outputs into standardized analysisready AIready datasets using Python R and cloudnative 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 mechanismbased toxicology exposureresponse concepts and in vivo study structures to guide data transformations and modeling strategies.
• Enhance crossstudy 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 cloudbased 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 worlds most ambitious and fastest-growing R&D Data Science organizations shaping how PSTS data powers nextgeneration therapies in the largest biomedical company on the planet. Your work will directly accelerate Johnson & Johnsons scientific discovery fuel AI innovation and impact patients globally.

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 & 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 external applicants please contact us via internal employees contact AskGS to be directed to your accommodation resource.

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