Senior Principal Computational Chemist/Toxicologist

Role Summary

The Senior Principal Computational Toxicologist (Chemistry-focused) will lead and support informatics-driven initiatives to integrate chemical and toxicology datasets aimed at improving the overall nonclinical drug discovery and development decision-making and processes, including but not limited to the reduction of currently required toxicity studies, the analysis, uptake and incorporation of new approach methods (NAMs) and the integration of multi-modal data to improve portfolio and study-level decision-making. This role combines advanced computational approaches with toxicology expertise to enable data-driven decision-making across drug discovery and development. The position will focus on building scalable data architectures and applying artificial intelligence/machine learning to transform drug safety assessment by advancing innovative approaches such as hybrid and virtual control study design implementation and multimodal predictive toxicology modeling.

Responsibilities

• Apply advanced R and/or Python programming for data processing, visualization, and statistical modeling.
• Implement machine learning workflows to predict toxicological outcomes and support AI-enabled safety assessments.
• Design, develop, curate, and maintain robust databases for chemical and toxicology data, ensuring data quality and compliance with Pfizer data standards.
• Collaborate with toxicologists, pathologists, data scientists, and informatics teams to integrate multi-modal datasets (chemical structures, in vitro/in vivo toxicology data) into next generation predictive toxicology models.
• Contribute to foundational data architecture strategies and implementation to enable AI-driven insights.
• Ensure data integrity, security, and adherence to regulatory requirements, while contributing to best practices for coding workflows, version control, and comprehensive documentation to support reproducibility and transparency.
• Communicate findings through reports, presentations, and publications to internal stakeholders and external scientific forums.
• Stay current with emerging computational toxicology methods and actively participate in team discussions to improve workflows and approaches.

Qualifications

• Education:
  • Master's in Computational Chemistry/Toxicology, Bioinformatics, Data Science, or related field with 10+ years of experience
  • Ph.D. in Computational Chemistry/Toxicology, Bioinformatics, Data Science, or related field with 5+ years of experience
• Technical Skills:
  • Deep expertise in R and/or Python for data analysis and modeling following coding best practices, including version control, structured workflows, documentation, and reproducibility standards.
  • Proven experience in database creation, management, and analysis particular with toxicology datasets
  • Expertise in machine learning techniques and their application in toxicology.
  • Understanding of data architecture principles to support AI workflows.
  • Soft Skills: Strong communication, collaboration, and problem-solving abilities.
• Preferred Qualifications:
  • Experience with cloud-based data platforms and big data technologies.
  • Knowledge of cheminformatics tools and toxicology ontologies and datasets (working with SEND formatted data).
  • Track record of publications in computational toxicology or related fields.
  • Domain Knowledge: Working knowledge of toxicology data, including chemical safety assessments and regulatory frameworks
• Additional notes: Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.

Physical Requirements

Ability to communicate clearly at internal and external meeting and across diverse teams. Office job involving computer use.

Travel / Environment

Limited travel for internal R&D site visits and to attend national and international scientific meeting, consortia and training opportunities.

Education

As above in Qualifications.