Guardant Health Sr. Bioinformatics Scientist, Machine Learning (Redwood City, CA, San Diego, CA or Seattle, WA)

At Guardant Health, we are committed to positively and significantly impacting patient health through technology breakthroughs that address long-standing unmet needs in oncology. As the leader in the field of liquid biopsy, Guardant Health has collected cancer genomic data from over 100,000 patients and is looking for bioinformatics scientists excited about analyzing genetic and epigenetic signals in this data to enable breakthroughs in cancer patient care by developing an assay for detection of cancer at an early stage. We are working at the forefront of scientific and technological developments with emphasis on results that enable clinical impact on real patients and you will contribute to this effort.

Here are some of our recent published results:

and the press release about the launch of 10,000-patient trial for evaluating the clinical impact of LUNAR blood test to detect colorectal cancer on average-risk population:


  • Develop, prototype, and analyze the performance of novel statistical models 
  • Explore and elucidate signals relevant to early cancer detection from large-scale NGS data
  • Participate in brainstorming sessions, maintain a highly productive and interactive work environment
  • Communicate analysis results to stakeholders across computational and experimental teams
  • Develop reproducible analyses for research and development activities
  • Provide written documentation and specifications


  • Dedicated to making a difference in a rapid-paced startup environment
  • Ph.D. in computational biology/bioinformatics, genomics, machine learning, or related fields + 3 years of relevant experience
  • Strong statistical fundamentals, especially in Bayesian probability, iterative model development, and hypothesis testing
  • Experienced in developing and implementing novel methods, and going beyond packaged algorithms
  • Experienced with analysis of genomic and epigenomic NGS data
  • Comfortable designing and executing analyses in an open-ended, data-limited setting
  • Experienced in the visualization of complex experiments to derive biological insights
  • Strong ability in a high-level scripting language (Python/R; Python preferred)


  • Cancer biology background
  • Experience in analyzing external genomic/epigenomic datasets (e.g. TCGA, ENCODE)
  • Familiar with high-performance computing infrastructures (e.g., SGE, Spark)
  • Experience leveraging AWS-based services  (e.g., EC2, S3) to speed analyses

We would like to talk with you about our exciting projects and career paths.



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