Principal Scientist
Bioinformatics
Posted on 9/15/2023
INACTIVE
Revolution Medicines

201-500 employees

Develops targeted therapies for RAS-addicted cancers.
Company Overview
REVOLUTION Medicines stands out in the oncology field for its unique approach to drug discovery, leveraging insights from nature and evolution to develop targeted therapies for RAS-addicted cancers. The company's robust drug discovery and medicinal chemistry capabilities have resulted in a deep pipeline of RAS inhibitors, with their most advanced product, RMC-4630, currently in a multi-cohort Phase 1/2 clinical program. This focus on genetic drivers and adaptive resistance mechanisms in cancer, coupled with their commitment to exploring mechanism-based dosing paradigms and in-pathway combinations, positions REVOLUTION Medicines as a leader in precision oncology.
Biotechnology

Company Stage

N/A

Total Funding

$1.1B

Founded

2014

Headquarters

Redwood City, California

Growth & Insights
Headcount

6 month growth

21%

1 year growth

51%

2 year growth

94%
Locations
San Carlos, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Data Analysis
CategoriesNew
Biology & Biotech
Requirements
  • A Ph.D. in bioinformatics, computational biology, statistics, applied math, physics or a related field with 8+ years of postdoctoral/industry experience leveraging quantitative methods to understand biology
  • Deep expertise in biological data analysis and visualization
  • Strong foundation in probability and statistics
  • Experience manipulating and analyzing large biological datasets in Python
  • Familiarity with standard computational and statistical methods to analyze high-throughput and high-content biological datasets (e.g. Tuba-seq, Perturb-seq, WES, scRNA-seq, spatial transcriptomics/proteomics, etc)
  • A “no task too big or too small” and “jump in where needed” mindset befitting of a small team starting up within a larger organization
  • Excellent communication, collaboration, and project management skills
Desired Qualifications
  • Oncology experience, particularly working with preclinical cancer model data (in vivo drug efficacy and genetic biomarkers) and clinical cancer data (clinicogenomics data), including an understanding of cancer genes, genomic alterations, gene complexes/pathways, and clinical outcomes
  • Ability to generate custom bioinformatics pipelines for the analysis of next-generation sequencing data
  • Experience synthesizing statistical/biological insights from multiple independent studies (i.e. meta-analysis) and from diverse experimental readouts (e.g. summarizing conclusions from joint in vitro, in vivo, and clinical data of various types)
  • Familiarity with software engineering best practices including around data modeling, pipelining, cloud computing, storage, and provenance
  • Familiarity with Python SDKs/APIs for CRUD (Create, Read, Update, Delete) access into Lab Information Management Systems (LIMS) to manage and analyze structured biological study (meta)data