Scientist, Genomics and Cancer Biology

Natera•San Carlos, CA

22h

About The Position

Natera is seeking a Scientist to drive multimodal genomics experiments for external BioPharma collaborations and internal discovery efforts. The role designs, executes, and interprets studies combining bulk and single-cell epigenomic and transcriptomic, spatial transcriptomic, and proteomic readouts on preclinical models and human patient samples. The Scientist translates complex datasets into biological insight for pharma partners and internal programs. This is a hands-on, independent-contributor position for a scientist early in their industry career. It requires strong cancer-biology judgment, technical depth across multiple genomic platforms, and comfort collaborating with computational scientists and project teams. The work includes end-to-end study execution, partner communication, internal discovery, data integration, workflow improvement, documentation, and mentoring. Natera is a global leader in cell-free DNA testing, focused on oncology, women’s health, and organ health. Its mission is to make personalized genetic testing and diagnostics part of standard care to support earlier, more targeted interventions. The company describes a collaborative workplace and offers competitive benefits and an inclusive, equal-opportunity work environment.

Requirements

Ph.D. in Cancer Biology, Molecular Biology, Genetics/Genomics, Biochemistry, or a related field.
Plus one of the following: at least 1 year of relevant industry experience in biotech, pharma, diagnostics, or equivalent; or a completed postdoctoral fellowship.
Demonstrated experience with at least two genomic modalities, such as epigenomic sequencing, RNA-seq, or proteomics, and with NGS library preparation and QC, as evidenced in high-quality publications.
Working proficiency in R and/or Python for genomic data analysis and visualization.
Ability to work across wet-lab and computational teams and communicate results clearly in writing and verbally.
Strong desire to drive the use of novel technological approaches to answer difficult biological questions.
Include the full list of first-author and co-authored publications.

Nice To Haves

Hands-on experience with single-cell RNA-seq, spatial transcriptomics, and/or spatial proteomics platforms, including sequencing-based or imaging-based spatial assays and multiplexed tissue imaging.
Experience handling FFPE or fresh-frozen tissue.
Familiarity with other high-dimensional platforms such as quantitative mass spectrometry.
Experience with human patient tissue and preclinical models, including cell lines, organoids, and GEMMs.
Familiarity with functional assays such as flow cytometry, viability assays, live-cell imaging, protein-interaction assays, and kinase assays.
Experience working in a collaborative environment.
Ability to manage timelines and deliverables across multiple concurrent projects.
Scientific independence and sound experimental design across multiple platforms.
Rigor in data quality and controls, and ability to distinguish signal from artifact.
Ability to collaborate with wet-lab, computational, and project-management colleagues.
Clear communication of complex data to technical and non-technical audiences, including pharma partners.
Ability to prioritize and reliably deliver against partner and program timelines.
Excellent presentation and writing skills.

Responsibilities

Drive multimodal genomics studies from experimental design through data delivery, including DNA methylation/hydroxymethylation, chromatin accessibility and occupancy, RNA-seq, proteomics, and phosphoproteomics.
Plan and execute single-cell RNA-seq, spatial transcriptomics, and spatial proteomics experiments, including sample preparation, platform workflows, quality control, and coordination with computational scientists on downstream analysis of cell types, cell states, and tissue architecture.
Translate collaborator and program questions, such as mechanism of action, therapeutic response, and biomarker discovery, into experimental designs, sample plans, and assay panels.
Support external BioPharma collaborations by contributing to study scoping, executing studies to agreed timelines, communicating progress and results to partners, and contributing to reports and presentations.
Lead internal discovery experiments that generate and test hypotheses about cancer cell state, treatment response, and candidate biomarkers, including potential applications to liquid-biopsy cfDNA/ctDNA profiling.
Generate high-quality NGS and, where applicable, mass-spectrometry datasets; perform library preparation and QC, manage sequencing runs, and flag technical or batch effects.
Integrate multimodal datasets using R and/or Python in partnership with computational scientists to identify signatures and prioritize candidates.
Implement and standardize laboratory workflows, including liquid-handling automation, to improve throughput and reproducibility.
Maintain rigorous documentation, sample tracking, and data provenance; contribute to SOPs, technical reports, manuscripts, and patents.
Mentor and train junior staff and collaborators in experimental design and technical methods as needed.