Senior Computational Genomics Scientist – Single-Cell

Preventive; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Preventive is hiring a Scientist or Senior Scientist to lead computational genomic analysis for low-input and single-cell studies of gene‑edited, heterogeneous, and multi‑species samples. This role will coordinate analytical strategy, pipeline development, data quality, and biological interpretation across genomic, epigenomic, and transcriptomic assays.

You will collaborate with experimental scientists on study design, controls, and data-driven decisions; there is potential for hands‑on wet‑lab

Qualifications

• BS+ and 4+ years in a relevant field.
• Fluency in R or Python; experience analyzing NGS data and building reproducible workflows.
• Working knowledge of molecular biology and NGS assay principles.

Responsibilities

• Own end‑to‑end analysis of genomic, epigenomic, and transcriptomic data, from raw reads and QC through statistical analysis, visualization, interpretation, and reporting.
• Analyze plate‑based single‑cell and trace‑input data; develop fit‑for‑purpose approaches for UMI handling, sparse data, low cell counts, contamination, ambient RNA, doublets.
• Genome‑wide assessment of edited samples via WGS
• Work with genome‑editing and assay‑development teams to define hypotheses, controls, replication, acceptance criteria, and follow‑up experiments
• Build, test, and maintain reproducible workflows using version control and container management
• Present analytical plans and results to computational, experimental, and leadership audiences; contribute code reviews and documentation
• Learn practical constraints of low‑input workflows through wet‑lab engagement; benchwork is not primary focus, but may occur

Skills

R

Python

NGS data analysis

Reproducible workflows

Molecular biology knowledge

Education

Bachelor's degree in a relevant field

Job description

Preventive is hiring a Scientist or Senior Scientist to lead computational genomic analysis for low-input and single-cell studies of gene‑edited, heterogeneous, and multi‑species samples. This role will coordinate analytical strategy, pipeline development, data quality, and biological interpretation across genomic, epigenomic, and transcriptomic assays.

You will collaborate with experimental scientists on study design, controls, and data-driven decisions; there is potential for hands‑on wet‑lab