Dedicated to oncology, women’s health, and organ health. Natera’s cell-free DNA tests help protect health and inform more personalized decisions about care. Backed by Lightspeed and Sequoia.
About the role
The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- PhD in Bioinformatics, Computer Science, Machine Learning, Statistics, or a related quantitative field, with 4 to 8+ years of post-PhD experience
- Hands-on experience in cancer genomics or epigenomics, experience with cell-free DNA or methylation sequencing data is a plus
- Strong foundation in quantitative reasoning, statistical analysis, and applied machine learning, experience with deep learning frameworks is a plus
- Proven track record of developing computational methods for high-throughput sequencing data analysis
- Strong programming skills, with hands-on experience in Python and its scientific library stack (pandas, NumPy, scikit-learn)
- Experience with Linux command-line tools, shell scripting, version control (Git), workflow managers (e.g., Nextflow, Snakemake), and cloud or HPC compute environments
More about this role
Natera is currently seeking a Lead Bioinformatics & Machine Learning Scientist to contribute to research and development within our Bioinformatics Research and Development team, focused on Epigenomics in Oncology. The team develops machine learning methods for early cancer detection from cell-free DNA methylation data. The ideal candidate will have a strong background in machine learning and statistical modeling, as well as genomics and sequencing data analysis. The successful candidate will be instrumental in developing and expanding state-of-the-art machine learning methods for early detection of cancer, and will provide technical leadership and mentorship within a highly collaborative team.
- Drive technical workstreams within a collaborative team that takes methods from problem definition through delivery of final classifiers to downstream validation teams
- Design, implement, and validate novel machine learning and statistical methods to solve problems in cancer diagnostics
- Establish and promote best practices in model interpretability, uncertainty estimation, and reproducibility
- Design robust feature engineering and extraction pipelines tailored to cfDNA methylation and...
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