Senior Scientist, Oncology Menlo Park, CA

Ready to redefine what's possible in molecular diagnostics?

Join a team of brilliant, passionate innovators determined to transform healthcare. At Billion To One , we've built a category-defining, publicly traded company on Nasdaq where transparency fuels trust, collaboration drives breakthroughs, and every contribution moves the needle on our mission to make life-changing diagnostics accessible to all. We don't just aim for incremental improvements; we build products that are 10x better than anything that exists today.

With over 700 employees, half a million patients helped, and one of the most successful IPOs in medical diagnostics history behind us, we're just getting started. Our scientists, engineers, sales executives, and visionaries are united by an unwavering commitment to changing the standard of care in prenatal and cancer diagnostics. This is where cutting‑edge science meets human compassion, and every innovation you contribute helps remove the fear of the unknown from some of life's most critical medical moments.

If you're driven by purpose, energized by innovation, and ready to help shape the future of precision medicine at scale, this is where you belong.

Billion To One  is seeking a Senior Scientist, Real‑World Evidence, Oncology to help unlock insights from our rapidly growing dataset of genomic profiles and real‑world clinical data
.

This role sits at the intersection of AI, genomics, oncology research, and clinical data science
. The scientist will develop models and analytical approaches that transform genomic and clinical data into actionable insights for research, clinical decision support, and future data‑driven products. The role will also build AI tools that support internal scientific operations—such as literature discovery, variant interpretation, and clinical trial or guideline tracking—while helping lay the foundation for future real‑world data products leveraging Billion To One ’s unique genomics and clinical dataset for pharmaceutical and research partners
.

A unique aspect of this role is the opportunity to work with Billion To One ’s proprietary dataset, combining genomic sequencing results from our Northstar oncology platform with real‑world medical records. Leveraging this rich dataset, the scientist will generate clinically meaningful insights and real‑world evidence (RWE) to improve treatment decisions and advance precision oncology. This role will report to the Chief Product Officer.

Responsibilities:

• Leverage Billion To One ’s integrated datasets of Northstar genomic sequencing results and real‑world clinical data from patients we serve to generate clinically meaningful insights and real‑world evidence (RWE).
• Develop AI and machine learning approaches that uncover patterns across genomic alterations, treatment histories, and patient outcomes, supporting internal research and improving how genomic test results inform clinical decision‑making.
• Develop AI‑powered tools that enhance the clinical utility of Billion To One ’s diagnostics
  , including systems that surface relevant medical records, literature evidence, clinical trials, and guideline information alongside Northstar test results to assist oncologists in making more personalized treatment decisions.

Qualifications:

• PhD in biology, biomedical sciences, medicine, computational biology, biomedical informatics, or a related field is required.
• Deep understanding of genomic data, oncology biology, and clinical medical data.
• Experience applying AI, machine learning, or advanced analytics to biomedical or healthcare datasets.
• Strong programming and data science skills (Python and modern ML frameworks).
• Experience working with real‑world clinical datasets (EHR, clinical records, registries, or similar).
• Ability to analyze and integrate multimodal biomedical datasets, including genomics, clinical data, and biomedical literature.
• Strong problem‑solving skills and ability to collaborate across interdisciplinary teams, including clinical, bioinformatics, and product groups.

Experience:

• Experience working with oncology real‑world datasets
  .
• Experience applying large language models (LLMs) or retrieval‑based AI systems to biomedical…