Senior Scientist, Cellular Genomics

Senior Scientist, Cellular Genomics

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.

Role 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.

  Basic Qualifications

  • 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
    • Experience using computational, statistical, machine learning, and approved agentic tools for high-dimensional data analysis, quality review, visualization, interpretation support, or hypothesis generation
    • Experience integrating genomic datasets with perturbational biology, pharmacology, translational datasets, or disease-model data to support mechanism-informed decision making
    • Hands-on or closely partnered experience with wet-lab genomic workflows, including single-cell, sequencing, spatial biology, tissue processing, or assay-development protocols
    • Experience with biomarker identification, translational medicine, or mechanism-informed drug-development decision support

      Physical/Mental Requirements

      • Ability to access and use a variety of computer software developed both in-house and off-the-shelf.
      • Occasional crouching, stooping, with frequent bending and twisting of upper body and neck.
      • Light to moderate lifting and carrying (or otherwise moving) objects including boxes and laptop computer with a maximum lift of 15-20 lbs.

        Additional Information:

        • Relocation support available
        • Work Location Assignment: On Premise
        • Last Day to Apply: September 7, 2026