Senior Computational Chemist
About The Position
Why Join MLCS in Medicine Design Pfizer Medicine Design brings together medicinal chemistry, discovery sciences, and MLCS to invent medicines that deliver meaningful benefits to patients. MLCS plays a central role in enabling data centric and ML-driven discovery, with opportunities to make impact directly on drug discovery projects through clear communication of actionable insights. Position Summary The Machine Learning & Computational Sciences (MLCS) organization within Medicine Design at Pfizer partners broadly across R&D to deliver computational, cheminformatics, and machine learning (ML) capabilities that accelerate drug discovery and development. MLCS supports medicinal chemistry and drug design teams by enabling data-driven decision making, scalable cheminformatics platforms, and impactful scientific applications across the discovery pipeline. We are seeking a Senior Computational Chemist with a strong cheminformatics background and a proven track record of independent scientific delivery. The ideal candidate is expected to lead applied computational and cheminformatics efforts across project teams, develop and shape technical approaches across multiple initiatives, and contribute durable, reusable capabilities that strengthen MLCS platform infrastructure and influence how computational chemistry and cheminformatics is best practiced across Medicine Design. With strong communication skills and adept at building productive partnerships, the successful candidate will thrive working in cross-functional teams with talented scientists across disciplines.
Requirements
- Ph.D. in Computational Chemistry, Cheminformatics, Computer Science, or related fields; or M.S. with substantial relevant industry experience.
- Deep understanding of cheminformatics concepts, including molecular representations, similarity methods, QSAR, virtual screening, chemical spaces
- Experience analyzing large, complex chemistry-related datasets.
- Strong proficiency in Python and cheminformatics toolkits (RDKit or equivalent).
- Experience with standard data science packages (numpy, pandas, etc)
- Proven experience applying ML models in real-world discovery projects.
- Practical experience with rapid application or UI prototyping in a scientific context.
Nice To Haves
- Prior experience in pharmaceutical or biotech drug discovery environments.
- Familiarity with deploying and scaling scientific workflows and applications.
- Experience with database design and processing (SQL, RestAPI).
- Experience in large-scale data handling and developing data pipelines.
- Familiarity developing code in collaborative manner (GitHub, code review & sharing).
- Familiarity working in HPC (e.g. SLURM) or cloud-based (AWS, GCP) environments.
- Familiarity with efficient use of agentic coding environments (GitHub Copilot or equivalent)
Responsibilities
- Chemistry Data Enablement (Data Science / Data Engineering): Lead the design, curation, and application of high-quality chemistry and pharmacology datasets used across multiple discovery programs.
- Architect and deploy data pipelines and transformations that enable scalable, reproducible data analytics and modeling.
- Set expectations for data quality and fitness-for-purpose in collaboration with scientific and platform stakeholders.
- Applied ML and Cheminformatics: Independently frame ambiguous medicinal chemistry problems into clear computational strategies and decision-support analyses.
- Drive the application of ML and Cheminformatics models to high-impact drug discovery questions.
- Critically assess model performance and limitations, guiding appropriate interpretation and use in project decisions.
- Rapid Prototyping & Front-End Development: Deliver robust, reusable, and well-documented scientific software aligned with modern best practices.
- Lead rapid prototyping of chemistry and cheminformatics applications to validate workflows and user experience with end users.
- Partner closely with chemists and software teams to evolve successful prototypes into production-ready solutions.
- Cross-Functional Collaboration & Delivery: Effectively bridge chemistry, data science, and software perspectives to align stakeholders around robust solutions.
- Influence projects through technical insight, credibility, and data-driven recommendations.
- Contribute to the scientific culture of MLCS through knowledge sharing, internal talks, and cross-team collaboration.
Benefits
- participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program
- 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution
- paid vacation, holiday and personal days
- paid caregiver/parental and medical leave
- health benefits to include medical, prescription drug, dental and vision coverage
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
