# Senior Data Scientist, CompBio at Insitro

- Company: Insitro
- What the company does: At insitro, we are building a different kind of drug company to bring better drugs faster to the patients who can benefit most. Through the power of machine learning (ML) and data at scale, we decode the complexities of biology to unlock transformative new... Backed by SoftBank VF, a16z and GV.
- Company website: https://www.insitro.com/
- Type: Startups
- Level: Senior
- Location: South San Francisco, CA
- Work setup: On-site
- Pay: $183K to $194K base salary per year (USD)
- Posted: 2026-08-28
- Apply by: 2026-10-12
- Apply: https://jobs.ashbyhq.com/insitro/ec4a278a-dd78-4e9c-a203-87e3e2f59e60
- Page: https://www.1752.vc/careers/jobs/insitro-senior-data-scientist-compbio/

## About the role

State-of-the-art technologies that measure multiple cellular aspects of in vitro biology are at the heart of insitro's efforts to accelerate drug development. Computational biology is key to elucidating the relationship between these phenotypes and human disease and translating them into actionable outcomes.

## What they're looking for

- Education & Tenure: Ph.D. in computational biology, systems biology, bioengineering, computer science, machine learning, or a related discipline, with 3+ years of working experience post-graduation
- Data Modality Depth: Hands-on experience with diverse data modalities, including at least one of the following: single-cell RNA-seq, fluorescence microscopy, spatial proteomics or transcriptomics, or label-free microscopy
- Statistical Foundation: Deep understanding of statistical modeling and data analysis, with a demonstrated ability to rigorously interpret complex datasets and generate mechanistic hypotheses
- Biological Grounding: An understanding of molecular biology or disease biology (e.g., neurological, cardiovascular, or metabolic disorders)
- Programming Skills: Strong programming ability and proficiency with Python scientific packages such as NumPy and pandas
- Publication Record: Meaningful contributions to high-quality work published in relevant computational biology, systems biology, life sciences, or biomedical venues

Tags: Data Science and Machine Learning