Guardant Health is a leading precision oncology company focused on helping conquer cancer globally through use of its proprietary blood tests, vast data sets and advanced analytics. The Guardant Health Oncology Platform leverages capabilities to drive commercial adoption, improve patient clinical outcomes and lower healthcare costs across all stages of the cancer care continuum. Guardant Health has launched liquid biopsy-based Guardant360®, Guardant360 CDx and GuardantOMNI® tests for advanced stage cancer patients. These tests fuel development of its LUNAR program, which aims to address the needs of early-stage cancer patients with neoadjuvant and adjuvant treatment selection, cancer survivors with surveillance, asymptomatic individuals eligible for cancer screening and individuals at a higher risk for developing cancer with early detection.
Job Description
Guardant Health is a leading precision oncology company focused on helping conquer cancer globally through use of its proprietary blood tests, vast data sets and advanced analytics. 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 vast amounts of cancer genomic data 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 assays for detection of residual disease after treatment. 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.
RESPONSIBILITIES
Analyze NGS data to support clinical collaborations and assay development efforts
Communicate analysis results to stakeholders across different teams
Generate new insights by analyzing external genomic & epigenomic sources, and internal data to improve product performance and suggest new product features
Develop predictive models to integrate different analytes for detecting tumor DNA in plasma
Exercise best practice in data analysis by writing reproducible code, clearly documenting the process, and contributing to a shared code base for analysis tools
ABOUT YOU
MSc with experience 6+ Years Relevant Experience or Ph.D. in computational biology, bioinformatics, genomics, machine learning or related fields
In depth understanding of concepts in data science, machine learning, model building
Proficiency with Python and tools/libraries for data analysis (jupyter, pandas, matplotlib, etc..)
Dedicated to make a difference in a rapid-paced startup environment
Experienced with analysis of genomic and epigenomic NGS data from raw reads to biological insight.
Experienced in visualization of complex experiments to derive biological insights
Proficiency with Linux command-line and version control tools (git and GitHub)
Experience with high-performance computing infrastructures (e.g., SGE)
Excellent communication and presentation skills, ability to work across functional teams with various backgroundss
PREFERRED
Cancer biology background
Experience with integrated multi-omic data analysis
Proficiency in building and testing machine learning models
Experience in analyzing public genomic/epigenomic datasets (e.g. TCGA, ENCODE)
Experience with good software engineering practices (e.g., unit testing, code documentation)
Qualifications
ABOUT YOU
MSc with experience or Ph.D. in computational biology, bioinformatics, genomics, machine learning or related fields
In depth understanding of concepts in data science, machine learning, model building
Proficiency with Python and tools/libraries for data analysis (jupyter, pandas, matplotlib, etc..)
Dedicated to make a difference in a rapid-paced startup environment
Experienced with analysis of genomic and epigenomic NGS data from raw reads to biological insight.
Experienced in visualization of complex experiments to derive biological insights
Proficiency with Linux command-line and version control tools (git and GitHub)
Experience with high-performance computing infrastructures (e.g., SGE)
Excellent communication and presentation skills, ability to work across functional teams with various backgroundss
PREFERRED
Cancer biology background
Experience with integrated multi-omic data analysis
Proficiency in building and testing machine learning models
Experience in analyzing public genomic/epigenomic datasets (e.g. TCGA, ENCODE)
Experience with good software engineering practices (e.g., unit testing, code documentation)
Additional Information
Guardant Health is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
