Director of Bioinformatics and Machine Learning

Natera's mission is to change the management of disease worldwide by using information from a simple blood draw to detect disease early and proactively inform treatment. We are seeking a Director of Bioinformatics and Machine Learning to lead technology and biomarker research for our cancer early detection programs. This leader will head a team of bioinformatics and machine learning scientists developing the foundation of our next generation of cell-free DNA (cfDNA) assays across multi-cancer early detection (MCED), tissue-free molecular residual disease (tfMRD), and single-cancer screening.

The ideal candidate is a hands-on scientific leader who sets technical direction and stays close to the work by challenging analyses, reviewing models, and prototyping when needed. They combine deep expertise in bioinformatics and machine learning with experience translating research into clinical diagnostics.

PRIMARY RESPONSIBILITIES:

• Define and execute research roadmaps for cancer early detection in partnership with Research, Product, Clinical, and Assay Development stakeholders.
• Lead, hire, and develop a team of machine learning and bioinformatics scientists, building a culture of scientific rigor, innovation, and ownership.
• Own the computational design of research studies, including cohort selection, confounder control, and validation strategies that prevent overfitting and data leakage.
• Partner with molecular biology teams to design experiments that generate data capable of answering the key scientific and clinical questions.
• Serve as the computational subject matter expert for leadership and cross-functional partners, communicating tradeoffs, risks, and recommendations clearly to technical and non-technical audiences.
• Advance Natera's scientific leadership through publications, conference presentations, and intellectual property.

QUALIFICATIONS: 

• PhD in Bioinformatics, Computer Science, Statistics, or a related quantitative field.
• 10+ years of post-PhD experience in industry or academic research, including 5+ years of direct people management leading technical teams of 5 or more scientists.
• Demonstrated track record of developing and deploying machine learning and statistical models on high-throughput sequencing data.
• Deep understanding of next-generation sequencing (NGS) data and large-scale genomic datasets, including sources of technical bias and batch effects.
• Strong communication skills, with experience influencing scientific direction at a senior level.

PREFERRED QUALIFICATIONS: 

• Experience in clinical diagnostics, including contributing to assays that reached analytical or clinical validation.
• Domain expertise in oncology, epigenomics, or cfDNA/liquid biopsy.
• Publication and/or patent record in computational oncology or machine learning.