Staff Machine Learning and Bioinformatics Scientist (Multi-Cancer Early Detection)

Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients.

PRIMARY RESPONSIBILITIES:

Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data

Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group

Prototype, test and productionize ML models using scalable infrastructure

Own key technical deliverables within larger projects and help shape the team’s research roadmap

Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies

Keep raising the bar through code and design reviews across projects

Translate complex results into clear stories for technical and non-technical audiences

Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence

QUALIFICATIONS:

PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD

Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data

Proven track record of innovation and technical leadership in complex method development projects

Expertise in deep learning and multimodal foundation models

Proficient in Python and its scientific computing ecosystem

Scientific rigor throughout the R&D process, with eagerness to teach and learn new computational methods and biology

Excellent communication skills and a collaborative approach across teams

Preferred Experience:

Familiarity with DNA methylation and other epigenomic data

Experience with cell-free DNA and liquid biopsy samples

Background in cancer genomics and diagnostics

Hands-on work with multimodal foundation models applied to biological data

The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.