​​Senior Associate Scientist, Cellular Genomics​

About this role

ROLE SUMMARY

We are seeking a highly motivated Senior Associate Scientist to join Pfizer’s Cellular Genomics team within Systems Immunology. This role is designed as an approximately 80% bioinformatics / computational genomics and 20% wet-lab genomics position, supporting the application of genomic and bioinformatic technologies to drug discovery, preclinical development, and translational medicine.

As a member of Cellular Genomics, this individual will focus primarily on data processing, quality assessment, reproducible analysis, and biological interpretation of genomics datasets, including single-cell, single-nucleus, spatial, bulk, and related multiomic profiling data. A smaller portion of the role will support hands-on wet-lab genomic workflows, including sample preparation, assay execution, and data generation for in vitro and in vivo studies under guidance from senior scientists and subject matter experts.

This role requires strong interest and developing experience in computational biology, bioinformatics workflows, scripting or analysis environments, and rigorous data quality practices, complemented by foundational wet-lab molecular biology and genomics experience sufficient to understand sample, assay, and platform constraints.

The ideal candidate is scientifically curious, analytically rigorous, and motivated to bridge computational analysis with experimental genomics. Success in this role requires meticulous attention to data integrity, reproducible analysis practices, strong problem-solving skills, and the ability to learn and apply innovative genomic and AI-enabled bioinformatic technologies.

ROLE RESPONSIBILITIES • Perform upstream data processing, quality assessment, and troubleshooting of sequencing runs, sample metadata, libraries, and genomic datasets using established computational infrastructure and analysis workflows. • Apply established computational biology and bioinformatic workflows, including AI-enabled tools where appropriate, to support quality assessment, biological interpretation, and reproducible reporting of experimental datasets under guidance from subject matter experts. • Generate, organize, and document analytical outputs, including quality-control summaries, exploratory analyses, figures, tables, and concise technical summaries for project teams. • Support project teams as an emerging computational genomics resource, contributing to discussions on experimental design, sample and metadata requirements, platform selection, data management, and interpretation of genomic readouts. • Contribute to evaluation, benchmarking, and qualification of new or improved bioinformatic workflows, genomic assays, platforms, instrumentation, and analytical approaches by executing defined analyses or experiments and documenting results. • Execute a focused wet-lab component of the role, including sample preparation, tissue dissociation, cell and nuclei isolation, nucleic acid extraction, library preparation, quality control, sequencing, and data generation as needed to support high-quality genomic datasets. • Assist with onboarding and training scientists on established genomics workflows, computational documentation practices, data-quality expectations, and best practices; contribute to presentations and technical updates as appropriate. • Stay current with advancements in single-cell genomics, spatial transcriptomics, multiomics, reproducible bioinformatics, and related agentic computational biology innovations. • Draft and maintain analysis plans, experimental plans, validation reports, work instructions, standard operating procedures, and other technical documentation. • Maintain accurate and compliant electronic lab notebook records and adhere to Pfizer quality, safety, reproducibility, and data integrity standards.

QUALIFICATIONS • Bachelor’s degree in Bioinformatics, Computational Biology, Genomics, Systems Biology, Computer Science & Molecular Biology, Data Science with biological applications, Biological Sciences with significant computational biology course work, or a related discipline with 0–3 years of relevant experience. • Master’s degree in Bioinformatics, Computational Biology, Genomics, Systems Biology, Data Science with biological applications, Biotechnology, Biological Sciences, or a related discipline with 0+ years of relevant experience. • Experience with genomics data analysis, quality control, visualization, or reproducible bioinformatic workflows for bulk RNA sequencing, single-cell and single-nucleus RNA sequencing, spatial transcriptomics, targeted sequencing, immune repertoire sequencing, epigenomics assays, or related genomic technologies. • Strong organizational, communication, and interpersonal skills, with the ability to work effectively in a collaborative research environment. • Demonstrated ability to prioritize multiple projects, manage timelines, and deliver high-quality work. • Strong problem-solving skills and commitment to scientific rigor, reproducibility, and data quality. • Self-motivated, adaptable, and eager to learn new technologies, workflows, and analytical approaches. • Experience using Python, R, command-line tools, notebooks, version-controlled workflows, or related analysis environments for genomics data processing and interpretation. • Foundational hands-on experience with molecular biology, sample preparation, sequencing library preparation, or genomics assay execution sufficient to integrate wet-lab context into computational analysis.

PREFERED QUALIFICATIONS • Experience with AI-enabled or agentic bioinformatic analysis tools, such as Claude Science, ToolUniverse, BIOMNI, or related platforms • Expertise in inflammation, immunology, neuro-inflammation, or translational medicine

  PHYSICAL/MENTAL REQUIREMENTS

Primarily computer-based analytical work requiring extended periods of focused data review, troubleshooting, and complex genomic data analysis; limited bench work may include sitting, pipetting, and liftin

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