Senior Bioinformatics Scientist – Research and Early Development
| Company | Guardant Health |
|---|---|
| Location | Palo Alto, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | PhD |
| Experience Level | Senior |
Requirements
- 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
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
Preferred Qualifications
- 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