Senior Scientist, Computational Biology (Contractor)

About Allogene:

Allogene Therapeutics, with headquarters in South San Francisco, is a clinical-stage biotechnology company pioneering the development of allogeneic chimeric antigen receptor T cell (AlloCAR T) products for cancer and autoimmune disease. Led by a management team with significant experience in cell therapy, Allogene is developing a pipeline of “off-the-shelf” CAR T cell product candidates with the goal of delivering readily available cell therapy on-demand, more reliably, and at greater scale to more patients.

About the role:

We are seeking a highly motivated Senior Scientist, Computational Biology to join our team. The Genomics & Bioinformatics function at Allogene is responsible for the full stack of computational biology and bioinformatics that underlies the company’s translational, clinical, and regulatory work — from multi-platform single-cell and flow cytometry analysis to clinical regulatory characterization to conference-ready data packages.

This is an execution-focused, high-ownership role working directly under senior ED-level direction. The person in this seat will own hands-on analysis across active programs, build and maintain durable analytical pipelines, and contribute to the regulatory and scientific record in ways that have direct program impact. There is no handholding and no bureaucratic overhead — this is a place where a strong computational biologist can do consequential science quickly. Candidates interested in developing new analytical capabilities, advancing computational approaches, and helping strengthen our bioinformatics function are strongly encouraged to apply.

This is not a support function. The analytical decisions made in this seat directly shape program strategy, regulatory packages, and external scientific communications. The person hired will work with cutting-edge allogeneic CAR-T data in an environment where computational biology is valued as a strategic scientific capability and an integral part of decision-making.

This role can be based out of our headquarters in South San Francisco, CA hybrid onsite 3 days a week or remote with travel to Allogene’s South San Francisco headquarters.

Responsibilities include, but are not limited to:

Multi-platform omics analysis

• Perform hands-on single-cell RNA-seq, BCR/TCR repertoire, NanoString, and flow cytometry data analysis across CAR-T clinical and research programs
• Integrate data across platforms and timepoints to support translational and clinical decision-making
• Conduct cell kinetics, persistence, and MRD analyses for ongoing trials
• Lead response biomarker correlate analyses — identifying computational signatures associated with clinical outcomes

Pipeline and data infrastructure

• Develop, document, and maintain reproducible analysis pipelines across platform data outputs
• Build and curate a regulatory- and inspection-ready repository of bioinformatics datasets, code, and metadata — structured for auditability and external review
• Contribute to GxP-adjacent tool validation documentation and data standards harmonization across programs

Regulatory and CMC support

• Generate analysis outputs and supporting documentation for clinical regulatory characterization work
• Support IND amendments and regulatory information requests requiring computational re-analysis
• Contribute bioinformatics methods sections and supplemental data for regulatory submissions
• Support process characterization omics analyses for CMC packages

Conference and publication support

• Provide analysis and figure generation for conference abstracts and posters (ASCO, ASH, ACR, ASCO-GU)
• Contribute to manuscript methods sections, supplementals, and reviewer response packages
• Interface with medical affairs to translate computational outputs into presentation-ready formats

Cross-functional and cross-program engagement

• Work across active programs
• Support competitive landscape monitoring of publicly released omics/bioinformatics datasets from competitor programs
• Collaborate with and train wet-lab scientists — translating computational outputs into actionable insights and building shared understanding across experimental and computational disciplines

Position Requirements & Experience:

• PhD in computational biology, bioinformatics, biostatistics, genomics, or a closely related quantitative field with 3+ years of industry experience in biotech or biopharma (post-PhD; substantive internship experience during graduate training also counted) or MS in computational biology, bioinformatics, biostatistics, genomics, or a closely related quantitative field with 10+ years of industry experience in biotech or biopharma
• Proficiency in R and Python for bioinformatics analysis; experience with standard single-cell frameworks (Seurat, Scanpy, or equivalent)
• Hands-on experience with 10x Genomics platforms and data (Chromium single-cell, VDJ, or Visium)
• Experience deploying and running analytical workflows on AWS (S3, EC2, or managed services such as SageMaker or Batch)
• Demonstrated experience with multi-omics or cross-platform data integration (scRNA-seq, BCR/TCR, flow cytometry, NanoString, bulk RNA-seq)
• Experience contributing to or supporting regulatory submissions (IND or equivalent regulatory filings) or GxP-adjacent documentation
• Strong written scientific communication — ability to produce analysis-ready documentation that meets regulatory and external review standards
• Ability to work autonomously under high-level scientific direction, prioritize across competing program timelines, and communicate clearly with non-computational stakeholders

Preferred experience:

• CAR-T or adoptive cell therapy experience — direct familiarity with the data types, clinical readouts, and translational questions specific to T-cell-based programs, or clinical trials data in general
• AI/ML background — experience applying machine learning to biological data (biomarker classification, dimensionality reduction, predictive modeling of clinical outcomes, or similar)
• Active use of LLMs for scientific productivity and development — using tools such as Claude, Copilot, or similar to accelerate code generation, data interpretation, literature synthesis, or documentation, with sound judgment about verification and limitations
• GenAI application development in a regulated or GxP-adjacent environment — hands-on experience building tools or workflows using large language models or generative AI, with real governance controls: audit trails, validation documentation, access controls, and change management consistent with regulated environments
• Experience working with or managing CRO/vendor relationships for bounded computational studies
• Familiarity with MRD analysis methodologies across oncology indications
• Experience with LIMS or ELN integration and reproducible workflow management (Snakemake, Nextflow, or equivalent)

We offer a chance to work with talented people in a collaborative environment. The expected hourly range for this role is $60 to $70 per hour. Actual pay will be determined based on experience, qualifications, geographic location, business needs, and other job-related factors permitted by law. As an equal opportunity employer, Allogene is committed to a diverse workforce. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, gender, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job-related characteristics or other prohibited grounds specified in applicable federal, state and local laws. We also embrace differences in experience and background, and welcome diversity of opinions and thought, designed to create a stronger and better Allogene that is focused on developing life-changing products for patients.

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