We believe conquering cancer is a big data problem. That’s why we built the world’s leading comprehensive liquid biopsy. This non-invasive tool for accessing and sequencing tumor DNA is used by thousands of oncologists to help tens of thousands of advanced cancer patients. We believe the boom in cancer data acquisition we helped launch will drive important discoveries and new products. We’re working on some exciting ones, including in early detection, where the impact on patients can be profound. We’ve raised more than $500 million from investors including Sequoia Capital, Khosla Ventures, OrbiMed, and SoftBank.
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 a member of the Bioinformatics development group, you will design wet lab studies, retrospective analyses, and simulations, develop and execute bioinformatics analysis plans, and author development reports. You will work closely with multiple teams across Guardant Health, including Bioinformatics, Software, Technology Development, Regulatory, and Operations. Your work will evaluate feasibility and reduce technical risk for development of critical features and studies in support of in-vitro diagnostic and companion diagnostic product development.
Work closely with molecular biologists to design and analyze feature development and feasibility experiments under design control
Develop and execute bioinformatics analysis plans with testable acceptance criteria
Conduct feasibility analyses and write development reports
Identify and solve problems proactively as needed
As a competitive candidate, you will have many of the the following training, skills, and experience:
IVD and/or Companion Diagnostic (CDx) development experience essential
Molecular diagnostics experience, with an emphasis on NGS approaches, desirable
Experience designing, analyzing, troubleshooting, and visualizing wet lab experiments
Demonstrable expertise in genome scale data analysis
Bioinformatics skills in genomics, sequence analysis, python or R scripting under version control
Awareness and experience with current landscape of bioinformatics tools
Working knowledge of statistical methods, including: conditional probability, linear modeling, goodness-of-fit tests, maximum likelihood, and bayesian models.
Attention to detail, with ability to write development reports
Commitment to reproducible research
Desire to contribute to personalized medicine and innovative cancer care
Ability to work under fast-paced startup environment
Education: PhD in Bioinformatics, Statistics, Computational Biology, Cancer Genomics, or related quantitative field Or MS and 3 years industry experience
All your information will be kept confidential according to EEO guidelines.