Senior Scientist, Computational Biology

Location
South San Francisco, CA, United States
Posted
Nov 04, 2020
Ref
4589575002
Hotbed
Biotech Bay
Required Education
Masters Degree/MBA
Position Type
Full time
JOB PURPOSE

A successful candidate will work closely with scientists and computational biologists to analyze NGS data and develop bioinformatics methods to solve exciting and challenging problems in cell and gene therapy, immunology, and cell biology. This person should be a team player and fantastic at cross-functional communication.

The ideal candidate should be excited about analyzing NGS and single cell data, able to develop computational workflows, and quickly prototype solutions. The candidate should have a technical background in NGS data analysis, which includes understanding the underlying algorithm for commonly used Bioinformatics tools. This candidate should be able to partner effectively with the Analytical Genomics team to analyze genomics data, and the Bioinformatics engineers to build and automate pipelines. The ability to be flexible, and to work in a highly collaborative environment and an agile team first mind-set will be critical to success.

PRIMARY RESPONSIBILITIES
  • Develop analysis workflows from existing algorithms or modify existing methods to analyze NGS data in Research, Analytical Genomics, Translational/Clinical Science, and Technical Operations. This includes development of novel Bioinformatics methods as needed to answer platform and biological questions to meet company objectives. Demonstrate validity of methods through prototypes and benchmarking using appropriate controls
  • Partner with internal stakeholders to design and analyze NGS experiments to provide quantitative information in cell and gene therapy and immunology
  • Identify, integrate, and analyze public datasets and databases (e.g. NGS, single cell, genetics) within the provided Sana infrastructure to answer critical questions to meet the goals of the Analytical Genomics & Translational Bioinformatics group; this will be performed in collaboration with the Computational Biology team in Cambridge
  • Proper documentation of code, workflows, and analyses including study reports for nonclinical and clinical studies
  • Work within the Bioinformatics/Computational Biology groups to review and test code, and refactor prototype workflows to production grade as necessary
  • Work cross functionally with scientists to design studies that are appropriately powered with the proper controls to meet experimental and business objectives
  • Closely collaborate with the Computational Biology group in Cambridge to share analysis workflows
  • Communicate to a broad audience with a range of technical, analytical, and biological expertise and present results on a regular basis at various group meetings

QUALIFICATIONS

Required Qualifications, Experience & Education
  • MS with 4+ years industry experience or PhD in computational biology, bioinformatics, or related discipline
  • 3+ years of hands-on experience with all steps of large-scale DNA- and RNA-Seq data analysis (FASTQ through variant calling and/or differential expression including QC) on an Illumina platform
  • Demonstrated proficiency in Python and R
  • 3+ years of experience with current bioinformatics tools such as STAR, SAMtools, Voom, edgeR/DESeq2, and kallisto/salmon
  • Experience with high performance computing (local or cloud) and proficiency in *ix
  • Routine use of version control (e.g. git, svn)
  • Strong prior experience with analyses of various library prep protocols for the Illumina platform
  • Demonstrated strong problem solving abilities and organizational skills
  • Must be detail oriented, self-motivated, flexible, and able to prioritize and manage several fast-paced projects concurrently
  • Outstanding verbal and written communication skills for technical and non-technical audiences
  • Demonstrated ability to work in cross-functional teams as a strong team player as well as independently

Preferred Qualifications & Education
  • Prior experience with single-cell sequencing analysis (e.g. Cell Ranger, Seurat, bustools plus kallisto) is a significant plus
  • Experience with documentation tools and software best practices in Python and R
  • Background in gene or cell therapy, immunology and/or cell biology
  • Familiarity with workflow languages (e.g. Nextflow, Snakemake)