Senior Bioinformatics Scientist, Research and Early Development

Company Description

Guardant Health is a leading precision oncology company focused on helping conquer cancer globally through use of its proprietary 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 commercially launched Guardant360®, Guardant360 CDx, Guardant360 TissueNext™, Guardant360 Response™, and GuardantOMNI® tests for advanced stage cancer patients, and Guardant Reveal™ for early-stage cancer patients. The Guardant Health screening portfolio, including the Shield™ test, aims to address the needs of individuals eligible for cancer screening.

Job Description

About the Role:

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 is looking for a bioinformatics scientist excited about conducting research and early development in an interdisciplinary environment to enable breakthroughs in cancer patient care. We are looking for an individual who will take ownership of innovative projects that utilize high-thoughput signals as well as novel assay development, and are geared to contribute to Guardant’s vision of cancer care through liquid biopsies, with a focus on early cancer screening, minimal residual disease detection, and therapy monitoring. This position is in the bioinformatics research and early development group.

We are working at the forefront of scientific and technological innovations, developing novel methodologies that deliver substantial clinical impact to patients. If this is something you are passionate about come join us!

Essential Duties and Responsibilities:

• Design, prototype, and analyze performance of novel statistical/machine learning models.

• Investigate data in model free contexts integrating fundamental statistical and visualization techniques and biological knowledge to derive insights.

• Apply modeling and model free approaches to large-scale genomics and epigenomic NGS data.

• Collaborate with Technology Development scientists on designing experiments to assess and improve assay performance.

• Work with cross-functional teams to discuss immediate and long-term product strategy.

• Participate in brainstorming sessions and collaborative efforts within a highly 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.

Qualifications

• Dedicated to making a difference in a rapid-paced, collaborative, startup-like environment

• Ph.D. in computational biology, bioinformatics, genomics, statistics, computer science, machine learning, or related fields

• Strong background in statistical fundamentals and analysis, including inference approaches and iterative model development, and hypothesis testing

• Experience developing and implementing novel methods, and going beyond packaged algorithms

• Experience with analysis of genomic and/or epigenomic NGS data

• 5+ years experience in industry/academia post-graduation

• Ability to design and execute analyses in an open-ended, data-limited setting

• Experience visualizing complex experiments to derive biological insights

• Proficiency with a high level scripting language (e.g. Python, R)

• Proficiency with Linux command-line and version control tools (git and GitHub)

• Excellent communication skills in an interdisciplinary environment 

Preferred

• Background in cancer biology or molecular biology

• Experience analyzing external genomic/epigenomic datasets (e.g. TCGA, ENCODE)

• Familiarity with high-performance computing infrastructures (e.g. SGE, Spark)

• Experience leveraging AWS-based services (e.g., EC2, S3) to speed analyses

Additional Information

Hybrid Work Model: At Guardant Health, we have defined days for in-person/onsite collaboration and work-from-home days for individual-focused time. All U.S. employees who live within 50 miles of a Guardant facility will be required to be onsite on Mondays, Tuesdays, and Thursdays. We have found aligning our scheduled in-office days allows our teams to do the best work and creates the focused thinking time our innovative work requi