Principal Data Scientist – R&d Dsdh - Preclinical Sciences & Translational Safety (psts)

J&J FAMILY OF COMPANIES

Spring House, PA, USA
Not specified
Machine learning model development
Data engineering pipelines
Python and/or r proficiency
Johnson & Johnson is seeking a Principal Data Scientist for their R&D DSDH in Preclinical Sciences & Translational Safety, responsible for leveraging machine learning and data engineering to drive safety evaluations and translational research. The ideal candidate will have a strong background in data science, toxicology, and pharmacokinetics, with experience in building data pipelines and developing predictive models

Job Summary

  • 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.
  • Develop and deploy ML/AI models to support safety signal detection, dose selection, PK/PD modeling, toxicology insights, and translational interpretation.
  • 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.

Matching Summary

Match Score: 85

Johnson & Johnson is seeking a Principal Data Scientist for their R&D DSDH in Preclinical Sciences & Translational Safety, responsible for leveraging machine learning and data engineering to drive safety evaluations and translational research. The ideal candidate will have a strong background in data science, toxicology, and pharmacokinetics, with experience in building data pipelines and developing predictive models.

Skills & Requirements

Must-have

  • Machine learning model development
  • Data engineering pipelines
  • Python and/or R proficiency
  • SQL and cloud tooling
  • Toxicology and PK/PD datasets

Nice-to-have

  • Scientific data formats
  • Ontologies and knowledge graphs
  • Cloud-based data architectures
  • Regulatory data standards

Key Requirements

  • MS or PhD degree
  • 3+ years of experience
  • Machine learning/data engineering experience
  • Biological/toxicology/PK/PD dataset experience
  • Python, R, SQL, cloud tooling

Work Rights

Not specified

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