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Scientist​/Senior Scientist; Genomic Analysis

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Preventive
Full Time position
Listed on 2026-01-12
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: Scientist/Senior Scientist (Genomic Analysis)

Scientist/Senior Scientist (Genomic Analysis)

Join to apply for the Scientist/Senior Scientist (Genomic Analysis) role at Preventive

Preventive Medicine is a public benefit corporation developing next‑generation reproductive‑genetics platforms to eliminate severe genetic disease at its origin. Our mission is to determine whether the newest generation of gene editing technologies can be used safely and responsibly to correct devastating genetic conditions for future children. If proven to be safe, we believe preventive gene editing could be one of the most important health technologies of the century.

About

the role

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.

Key Responsibilities
  • Safety / off‑target profiling: Genome‑wide assessment of edited samples via WGS (short/long‑read), targeted capture, and GUIDE‑seq/CIRCLE‑seq/CHANGE‑seq derivatives with orthogonal validation; call SNVs/indels/SVs/CNVs and quantify mosaicism/allele‑specific edits.
  • Characterization of edited samples: Execute plate‑based single‑cell NGS (e.g., Smart‑seq3/Smart‑seq2; plate‑based scATAC/CUT&Tag) for genomic, epigenomic, and transcriptomic profiling of very small, heterogeneous samples where droplet methods are infeasible.
  • Computational analysis: Build and maintain reproducible pipelines (Nextflow/Snakemake, containers); 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).
  • 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.
Qualifications

Minimum

  • BS+ in a relevant field; 2+ years biotech experience.
  • Fluency in R or Python; experience analyzing NGS data (alignment, QC, variant calling) and building reproducible workflows (Git, containers).
  • 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.

Preferred

  • Previous experience in a startup environment (comfort with fast cycles, evolving priorities, and cross‑functional collaboration).
  • 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; cloud/HPC.
Seniority level
  • Entry level
Employment type
  • Full‑time
Job function
  • Research, Analyst, and Information Technology

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Position Requirements
10+ Years work experience
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