Senior Bioinformatician: Scale Omics & ML for Human Tissues

Vivodyne; Brisbane (CA); On-site; USD 214,000 - 245,000; Full time

Job summary

Vivodyne is expanding its Software & Data Science team in San Francisco, seeking a Bioinformatician to develop novel analytical methods for single-cell and multi‑omics data. You will shape data processing, storage, and interpretation while building scalable, production‑grade pipelines with cross‑functional partners.

The role emphasizes ownership of both science and engineering decisions, partnering with experimental biologists and software engineers to deliver robust, publication‑quality

Qualifications

• Ph.D. in computational biology or a related quantitative field.
• 2–5 years of post‑PhD experience; industry experience preferred.
• Strong Python for bioinformatics with Scanpy; breadth with R/ Bioconductor is valued.
• Deep experience with scRNA‑seq and proteomics workflows.
• Comfort with Unix/Linux, git, containers, and cloud/workflow tools.

Responsibilities

• Develop and evaluate computational methods for scRNA‑seq, bulk RNA‑seq, secretomics, and proteomics data.
• Benchmark and adapt methods for perturbation modeling, causal inference, and multi‑omics integration.
• Architect end‑to‑end analysis workflows in Python and/or R to scale datasets.
• Collaborate with engineers to productionize pipelines and ensure robust data storage.
• Translate analyses into clear insights for biologists, engineers, and stakeholders.

Skills

Python bioinformatics

Scanpy

scverse

R Bioconductor

Seurat

Monocle

Unix/Linux

AWS

Nextflow

Git / CI-CD

Education

Ph.D. in Computational Biology

Tools

Nextflow

Snakemake

Git

Containers

CI/CD

TileDB-SOMA

Job description

Vivodyne is expanding its Software & Data Science team in San Francisco, seeking a Bioinformatician to develop novel analytical methods for single-cell and multi‑omics data. You will shape data processing, storage, and interpretation while building scalable, production‑grade pipelines with cross‑functional partners.

The role emphasizes ownership of both science and engineering decisions, partnering with experimental biologists and software engineers to deliver robust, publication‑quality