Scientist/Senior Scientist (Genomic Analysis) at Preventive in South San Francisco, CA

Job description

• Preventive is hiring a Scientist or Senior Scientist to lead genomic analysis across wet‑lab experimentation and computational pipelines. You will design, execute, and analyze ultra‑low‑input NGS experiments from heterogeneous, multi‑species samples with emphasis on epigenetic characterization and comprehensive safety/off‑target profiling. The role spans low‑input method development, specialized library prep, and computational analysis.

Responsibilities

• Characterization of edited samples: Execute plate-based single-cell/low-input NGS (e.g., Smart-seq3/Smart-seq2; plate-based scATAC/CUT&Tag; EMseq2) for genomic, epigenomic, and transcriptomic profiling of very small, heterogeneous samples where droplet methods are infeasible.
• Computational analysis: Build and maintain reproducible analysis pipelines; perform QC, UMI handling, multi‑genome alignment, ambient RNA/doublet removal, batch correction/integration, differential analysis, trajectory/RNA velocity; support cross‑species analyses (liftover/custom references).
• Biological interpretation: Design, defend and execute analyses of high-dimension NGS datasets to identify and validate perturbations from baseline biology; design experiments and benchmarks to compare strengths and limitations of NGS-based assays.
• Safety / off‑target profiling: Genome‑wide assessment of edited samples via WGS (short/long‑read); call SNVs/indels/SVs/CNVs and quantify mosaicism/allele‑specific edits.
• Experimental design & wet lab: Partner with genome‑editing teams on controls and study design; design guides/donors; perform cloning and trace‑input library prep with rigorous QC and documentation.

Requirements

• Minimum qualifications
• BS+ and 4+ years in a relevant field (we care more about your demonstrable experience than your formal education).
• Fluency in R or Python; experience analyzing NGS data (alignment, QC, variant calling) and building reproducible workflows.
• Demonstrated expertise with low‑input/single‑cell assays (e.g., scRNA‑seq, epigenomic profiling, long‑read).
• Proficiency in molecular biology (library prep, cloning, PCR/qPCR, nucleic‑acid QC) and sterile mammalian cell culture.
• End‑to‑end off‑target discovery/validation for gene‑edited samples in preclinical studies, leading to submission to regulatory bodies
• Single‑cell analysis beyond defaults (batch correction, trajectory/velocity, doublet/ambient handling in low‑cell‑number datasets).
• Genome‑wide variant analysis for edited samples (SNVs/indels/SVs/CNVs; low‑VAF mosaic detection; integration‑site mapping) and epigenomic characterization.
• Experience with very early developmental or gamete samples across species.
• Spatial transcriptomics/epigenomics
• Previous experience in a startup environment (comfort with fast cycles, evolving priorities, and cross‑functional collaboration).

Skills

Required

• R or Python
• Reproducible workflows
• Sterile mammalian cell culture

Preferred

• Spatial transcriptomics/epigenomics
• Startup environment experience