Pre Clinical Safety Data Scientist

Pre Clinical Safety Data Scientist

Kenvueは現在、a:

Kenvueで、日常のケアの並外れた力を実感します。100年以上にわたる伝統を基盤に、科学に根ざした当ホテルは、ニュートロジーナ®、アヴェーノ®、タイレノール®、リステリン®、ジョンソンズ®、バンドエイド®など、すでにお馴染みのアイコニックなブランドを展開しています。科学は私たちの情熱です。ケアは私たちの才能です.

私たちのグローバルチームは~22,000人の優秀な人々で、すべての声が重要で、すべての貢献が評価される職場文化を持っています。私たちは洞察に情熱を注いでいます。 革新とお客様に最高の製品を提供することに取り組んでいます。専門知識と共感力を持つKenvuerであることは、毎日何百万人もの人々に影響を与える力を持つことを意味します。私たちは人を第一に考え、熱心に気を配り、科学で信頼を勝ち取り、勇気を持って解決します。そして、素晴らしい機会があなたを待っています!私たちと一緒に、私たちの、そしてあなたの未来を形作りましょう。詳細についてはhere。

Manager NA-Toxicology

North America, United States, New Jersey, Summit

ハイブリッド

In this role, you will leverage advanced computational, omics, and data science approaches to support pre-clinical safety and product development decisions, integrating AI and machine learning tools to accelerate insights and enhance scientific workflows. You will apply modeling, simulation, and predictive analytics to guide candidate selection, risk assessment, and formulation strategies, while generating and validating hypotheses using internal and external data.

Working closely with cross-functional partners across R&D, Medical Safety, and Regulatory, you will translate complex data into clear, actionable insights that inform strategy and innovation. This is a 2–3 year assignment.

• Omics & Computational Method Development
  :
  Designs and implements innovative omics‑based and computational toxicology approaches to address key challenges in product development.

• AI & Data Science Integration
  :
  Incorporates AI tools, large language models (LLMs), and agentic workflows into daily scientific operations to accelerate discovery, documentation, review, and insight generation.

• Modeling, Simulation & Predictive Analytics
  :
  Utilizes modeling, simulation, and machine‑learning–driven predictions to support decision‑making for candidate selection, formulation optimization, and risk assessment.

• Hypothesis Generation & Validation: Leverages literature, public datasets, and internal data—or proposes new experiments—to validate computational models and test model‑generated hypotheses.

• Cross‑Functional Scientific
  
  Collaboration:
  
  Partners closely with teams across R&D, Medical Safety, and Regulatory Affairs to integrate computational findings with experimental evidence and guide project strategy.

• Scientific Communication & Reporting
  :
  Communicates complex computational approaches and data-derived insights to technical and non‑technical audiences through clear reports, presentations, and scientific deliverables. Contributes to manuscripts, conference materials, and external collaborations.

• Broad Scientific Expertise & Literature Insight: Maintains broad and current knowledge of toxicology, computational biology, and data science trends, actively interpreting and applying emerging research to R&D initiatives.

• Candidates must be legally authorized to work in the U.S. and must not require sponsorship for employment visa status now or in the future (e.g. H1-B status)

• M.S. or Ph.D. (preferred) in Data Sciences, Computational & Integrative Sciences or equivalent , with proven track record (e.g publications, posters, presentations) of applying modeling, simulation, and computational approaches for real world academic or industry toxicology/health sciences studies

• You’re available to complete a 2-year assignment, with the potential to extend to 3 years in Summit, NJ (Hybrid)

• Strong proficiency with programing languages such as SQL, Python, R,…