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
- 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.
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 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.
Preferred Qualifications
- 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 collaboratively (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).
Additional Information / Application
- Work location assignment: Hybrid.
- Last date to apply: May 1st, 2026.
Benefits (as stated)
- Annual base salary range: $106,000.00 to $176,600.00.
- Eligible for participation in Pfizerβs Global Performance Plan with a bonus target of 15.0% of base salary and eligibility for share-based long-term incentive program.
- 401(k) with Pfizer matching contributions and additional Pfizer retirement savings contribution.
- Paid vacation, holidays, personal days; paid caregiver/parental and medical leave.
- Health benefits including medical, prescription drug, dental, and vision coverage.