Senior Data Scientist, Computational Biology

DELFI Diagnostics, Inc.•Palo Alto, CA

1d•$130,000 - $165,000•Hybrid

About The Position

DELFI Diagnostics is developing next-generation, blood-based cancer detection tests using advanced machine-learning methods on whole-genome sequencing data. The DELFI platform utilizes fragmentomics, analyzing cell-free DNA (cfDNA) fragment patterns to detect cancer. Their first product, FirstLook Lung, is a laboratory-developed screening test for individuals eligible for lung cancer screening. The company is committed to improving health outcomes globally, especially for underserved populations, by leading with science, building inclusively, and prioritizing teamwork and empathy.

Requirements

Doctoral degree in Computational Biology, Bioinformatics, Data Science, or a related field with 2+ years of industry experience; or, Master's with 3+ years of industry experience; or, Bachelor’s with 5+ years of industry experience.
Hands-on experience with high-dimensional biological datasets across multiple biomarkers and molecular data types.
Background in cancer biology or oncology-focused research.
Demonstrated ability to own projects end-to-end with limited oversight.
Demonstrated ability to use experimental findings to drive decisions for future research or product directions.
Strong collaborator with wet lab and experimental teams.
Proficiency in Python; experience with cloud environments (AWS preferred).

Nice To Haves

Experience with cfDNA, liquid biopsy, and NGS-based platforms.
Familiarity with ML modeling in a biological context.
Experience in a regulated diagnostics or clinical setting.

Responsibilities

Own end-to-end analysis of high-dimensional molecular workstreams across multiple data modalities, from data processing through interpretation and communication of results.
Contribute to classifier design, development, and validation to detect cancer in prospective clinical studies.
Adapt external, state-of-the-art representation and foundation models for DELFI’s internal applications.
Collaborate closely with Assay, Software, and Clinical teams to evaluate and integrate emerging data types into analytical pipelines.
Support data science coverage across active studies, including assay research, characterization and validation.
Work effectively in a fast-moving environment where priorities shift and self-direction is expected.