Senior Computational Chemist
Pfizer
August 12, 2026
Remote friendly (La Jolla, CA)
United States
Clinical Research and Development
Key Responsibilities
- Lead the design, curation, and application of high-quality chemistry and pharmacology datasets across discovery programs.
- Architect and deploy data pipelines and transformations for scalable, reproducible data analytics and modeling.
- Set expectations for data quality and fitness-for-purpose with scientific and platform stakeholders.
- Independently frame ambiguous medicinal chemistry problems into computational strategies and decision-support analyses.
- Drive ML and cheminformatics models to high-impact drug discovery questions.
- Critically assess model performance and limitations to guide interpretation and use in project decisions.
- Deliver robust, reusable, well-documented scientific software using modern best practices.
- Lead rapid prototyping of chemistry and cheminformatics applications to validate workflows and user experience.
- Partner with chemists and software teams to evolve prototypes into production-ready solutions.
- Bridge chemistry, data science, and software perspectives; influence projects with technical insight and data-driven recommendations.
- Contribute to MLCS culture through knowledge sharing, internal talks, and cross-team collaboration.
Required Qualifications
- Ph.D. in Computational Chemistry, Cheminformatics, Computer Science, or related fields; or M.S. with substantial relevant industry experience.
- Deep understanding of cheminformatics (molecular representations, similarity methods, QSAR, virtual screening, chemical spaces).
- Experience analyzing large, complex chemistry-related datasets.
- Strong Python proficiency and cheminformatics toolkits (RDKit or equivalent).
- Experience with data science packages (e.g., numpy, pandas).
- Proven ML application in real-world discovery projects.
- Experience with rapid application/UI prototyping in a scientific context.
Preferred Qualifications
- Prior pharmaceutical/biotech drug discovery experience.
- Experience deploying/scaling scientific workflows and applications.
- Database design/processing (SQL, REST API); large-scale data pipelines.
- Collaborative coding (GitHub, code review).
- HPC (SLURM) and/or cloud (AWS, GCP).
- Familiarity with agentic coding tools (e.g., GitHub Copilot or equivalent).
- Lead the design, curation, and application of high-quality chemistry and pharmacology datasets across discovery programs.
- Architect and deploy data pipelines and transformations for scalable, reproducible data analytics and modeling.
- Set expectations for data quality and fitness-for-purpose with scientific and platform stakeholders.
- Independently frame ambiguous medicinal chemistry problems into computational strategies and decision-support analyses.
- Drive ML and cheminformatics models to high-impact drug discovery questions.
- Critically assess model performance and limitations to guide interpretation and use in project decisions.
- Deliver robust, reusable, well-documented scientific software using modern best practices.
- Lead rapid prototyping of chemistry and cheminformatics applications to validate workflows and user experience.
- Partner with chemists and software teams to evolve prototypes into production-ready solutions.
- Bridge chemistry, data science, and software perspectives; influence projects with technical insight and data-driven recommendations.
- Contribute to MLCS culture through knowledge sharing, internal talks, and cross-team collaboration.
Required Qualifications
- Ph.D. in Computational Chemistry, Cheminformatics, Computer Science, or related fields; or M.S. with substantial relevant industry experience.
- Deep understanding of cheminformatics (molecular representations, similarity methods, QSAR, virtual screening, chemical spaces).
- Experience analyzing large, complex chemistry-related datasets.
- Strong Python proficiency and cheminformatics toolkits (RDKit or equivalent).
- Experience with data science packages (e.g., numpy, pandas).
- Proven ML application in real-world discovery projects.
- Experience with rapid application/UI prototyping in a scientific context.
Preferred Qualifications
- Prior pharmaceutical/biotech drug discovery experience.
- Experience deploying/scaling scientific workflows and applications.
- Database design/processing (SQL, REST API); large-scale data pipelines.
- Collaborative coding (GitHub, code review).
- HPC (SLURM) and/or cloud (AWS, GCP).
- Familiarity with agentic coding tools (e.g., GitHub Copilot or equivalent).