Senior Scientist, Cellular Genomics

SUMMARY   We are seeking a highly productive and motivated senior scientist to join the Cellular Genomics group within Pfizer’s Inflammation and Immunology Research Unit. This role is approximately 80% computational biology and 20% wet-lab genomics, with primary accountability for analyzing, integrating, and interpreting high-dimensional single-cell, spatial, and multi-omics datasets that support selected Inflammation and Immunology drug development programs. The individual will apply rigorous computational workflows, statistics, reproducible analysis in R and Python, standard bioinformatics pipelines, and approved agentic computational biology tools to generate decision-relevant biological insight from complex genomic datasets. The role will also include targeted wet-lab genomic contributions, including study design input, sample-processing strategy, assay-quality review, and limited hands-on support for single-cell, sequencing, or spatial workflows when needed to ensure data quality and interpretability. The candidate should be able to connect disease biology, perturbational responses, pharmacology, and translational context into mechanistic interpretations of drug-candidate effects in collaboration with project scientists, wet-lab genomics experts, translational teams, and computational biology partners. Independent scientific judgment, strong quantitative reasoning, reproducible computational practice, and practical problem solving in systems biology are required.

RESPONSIBILITIES    Lead computational analysis of single-cell, spatial, and multi-omics datasets, including quality assessment, preprocessing, statistical analysis, visualization, biological annotation, and reproducible interpretation.  Translate high-dimensional genomic data into mechanistic hypotheses, biomarker concepts, pharmacology interpretation, and decision-relevant insights for cross-functional drug development teams.  Apply and adapt established bioinformatics pipelines, statistical workflows, R/Python-based analyses, approved agentic computational tools, and data-management practices in collaboration with internal and external partners.  Integrate cellular genomics data with disease biology, perturbation biology, pharmacology, translational datasets, and project-specific hypotheses to support mechanism-informed portfolio decisions.  Provide wet-lab genomics input for study design, sample-collection strategy, assay selection, data-quality requirements, and interpretation of single-cell, sequencing, or spatial profiling workflows.  Contribute limited hands-on wet-lab execution, troubleshooting, or workflow support when needed to ensure genomic data quality, while maintaining primary focus on computational analysis and biological interpretation.

BS with 6+ years, MS with 4+ years, or PhD with 0-3+ years of relevant experience in computational biology, genomics, systems biology, immunology, bioinformatics, or a related discipline  Strong practical experience analyzing single-cell, spatial, transcriptomic, epigenomic, or other high-dimensional genomic datasets using reproducible computational workflows  Proficiency in R, Python, statistics, data visualization, quality control, standard bioinformatics pipelines, and interpretation of multi-omics data in biological or pharmacological context  Hands-on experience of wet-lab genomic assay workflows, including sample processing, sequencing, single-cell, or spatial profiling methods sufficient to evaluate data quality and guide study design    PREFERRED QUALIFICATIONS   2+ years of computational biology or bioinformatics experience analyzing single-cell, spatial, sequencing, or multi-omics datasets in inflammation, immunology, neuroinflammation, or autoimmunity indications  Experience with version-controlled workflows, command-line tools, scalable data processing, statistical modeling, visualization, and reproducible reporting