Menlo Park, California
Commensurate with experience
May 23, 2017
Jul 23, 2017
Full Time



GRAIL, Inc., is developing differentiated platforms for the early detection of cancer. These platforms combine approaches to ultradeep sequencing of circulating, cell-free nucleic acids with innovative clinical programs of the scale and quality required to generate strong scientific and clinical evidence of their utility. GRAIL’s software and computational biology efforts are commensurate to the size and complexity of the resulting data sets. We are seeking passionate and talented individuals to join us in realizing our mission, which has the potential to dramatically reduce the global burden of cancer.


In this role, you’ll build a team at the forefront of modern genomics to set the company’s research directions in bioinformatics, associated pipeline development, and statistical methods. You will develop and execute statistical analysis plans operating across GRAIL’s data sets, public data, and data from collaborators in academia and industry. You will partner with assay development teams to develop robust experimental and process statistics functions that result in optimal design of experiments and the highest quality and most reproducible data from GRAIL’s laboratory pipelines. You will build a research capability and partner with our data science (machine learning) team to develop new statistical methods. You'll represent our company to external scientific audiences. Most importantly, you will be responsible for developing a culture of statistical objectivity throughout the company.


  • Build GRAIL’s deep bench of knowledge in bioinformatics, statistics, and their combinations
  • Create and execute analyses operating on external and internal data sets
  • Build and develop a team of bioinformatics scientists, statisticians, and engineers
  • Develop computational statistical research programs which address fundamental questions in GRAIL’s product development efforts
  • Collaborate with GRAIL’s other teams, including our clinical, R&D, and machine learning teams, to produce unique analytical tools and approaches and act as an evangelist for their use.
  • Promulgate approaches and build tools that preserve scientific rigor and quality and which maintain GRAIL’s statistical culture
  • Formulate and direct external collaborations
  • Maintain an active external scientific presence


  • M.D./Ph.D. or Ph.D. in Bioinformatics, Computational Biology, Statistics, Biological Sciences, Cancer Biology, Genetics, Genomics, Computer Science, or equivalent preparation and experience.
  • An international scientific reputation as demonstrated by highly cited publications, impactful tools or data sets used by the scientific community, presentations at international conferences, and awards.
  • Minimum of 10 years relevant experience in positions of increasing responsibility.
  • A track record of building tool and products that have been widely adopted and impactful.
  • Consistent record of hiring and development of productive teams.
  • History of success working in cross-functional environments
  • Deep understanding of modern tools and pipelines in genomics for processing and analysis of primary data, including quality metrics, somatic and structural variant calling, assembly, etc. and approaches to functionally analyze these data.
  • An understanding of experimental limitations of next generation sequencing experiments as applied broadly in cancer.
  • Demonstrated ability to apply these skills to uncover new biological insights.


  • 5 years of industry experience preferred
  • Validated ability as a software engineer. Good scientific software engineering practice.
  • Excellent statistical understanding of the underlying limitations of analytical approaches.
  • Excellent oral and written communication skills
  • Familiarity with regulated industry practices
  • Clinical product development experience

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.