Senior Scientist I, Cancer Genomics, Clinical Biomarker Development
Revolution Medicines
Summary
In this role you will join the Cancer Genomics group in Clinical Biomarker Development, which sits within the Translational Medicine department to develop biomarkers, technology, and computational strategies for our RAS(ON) inhibitor programs. You will drive the application of advanced genomics analyses to maximize insight generation from clinical samples in our Phase I-III studies. This role offers the chance to work in a collaborative and innovative environment, including on cross-functional teams with other computational scientists, biomarker leads, biostatisticians, and preclinical scientists.
Job description
The Opportunity
In this role you will join the Cancer Genomics group in Clinical Biomarker Development, which sits within the Translational Medicine department to develop biomarkers, technology, and computational strategies for our RAS(ON) inhibitor programs. You will drive the application of advanced genomics analyses to maximize insight generation from clinical samples in our Phase I-III studies. This role offers the chance to work in a collaborative and innovative environment, including on cross-functional teams with other computational scientists, biomarker leads, biostatisticians, and preclinical scientists.
As a Cancer Genomics Senior Scientist I in Clinical Biomarker Development, you will:
- Apply advanced analytics and genomics solutions to clinical biomarker data to inform research & development
- Integrate multi-omics datasets to interrogate disease biology and prognosis, mechanisms of resistance, and predict drug response
- Collaborate with cross-functional teams, managing interactions with key stakeholders to deliver robust biomarker analyses and recommend follow-up actions
- Communicate results to expert and non-expert audiences, including internal cross-functional team members and external collaborators, through scientific publications and presentations
Required Skills, Experience and Education
- A Ph.D. in Cancer Genomics, Genetics, Computational Biology, Bioinformatics, or similar degree.
- A minimum of 2 - 8 years post-PhD experience analyzing cancer genomics data (post-doc, biotech, pharma, diagnostics, or combination).
- A strong foundation in cancer biology, preferably with an understanding of RAS/MAPK signaling pathways in pancreatic, lung, or colorectal cancer.
- Proficiency programming in R and/or Python, and expert in clearly documenting work with a version control system (git).
- Experienced in Linux and the cloud, including HPC clusters and command line interface, and developing genomics workflows for large scale NGS datasets.
- Experienced analyzing ctDNA or other liquid biopsy data derived from blood samples.
- Experienced in the interrogation of DNA sequence data derived from tumor tissue, such as gene-panel, whole-exome or whole-genome data and downstream analytics (clonality estimates, copy number variation, chromosomal instability, mutational signatures, etc).
- Practiced in commonly used tools and methods for DNA data analysis (GATK, Bioconductor, etc) and in utilizing publicly available datasets (TCGA, cBioPortal) to interrogate cancer genomics data.
- Strong understanding of statistics and the ability to generate robust predictive models with multidimensional data.
- Strong interpersonal, verbal and written communication skills; proactive, self-motivated, and adaptable in a dynamic environment.
- Demonstrated ability to translate complex data into clear biological insight, and to influence project direction through data-driven scientific inquiry.
Preferred Skills
- Experienced analyzing clinical endpoints (ORR, PFS, OS) and/or experienced with clinico-genomic RWE analytics.
- Longitudinal ctDNA data analysis for predicting clinical endpoints (ORR, PFS, OS).
- Deep knowledge of pancreatic, lung, or colorectal cancer, preferably including how progression, response and resistance may be mediated by biomarkers detected in tissue and/or blood biomarkers.
Requirements
- Ph.D. in Cancer Genomics, Genetics, Computational Biology, Bioinformatics, or similar degree.
- Minimum of 2-8 years post-PhD experience analyzing cancer genomics data.
- Strong foundation in cancer biology, preferably with understanding of RAS/MAPK signaling pathways in pancreatic, lung, or colorectal cancer.
- Proficiency in R and/or Python, and expert in documenting work with version control (git).
- Experience with Linux and cloud, including HPC clusters and command line interface, and developing genomics workflows for large scale NGS datasets.
- Experience analyzing ctDNA or other liquid biopsy data derived from blood samples.
- Experience in interrogation of DNA sequence data from tumor tissue (gene-panel, whole-exome, whole-genome) and downstream analytics (clonality, CNV, chromosomal instability, mutational signatures).
- Practiced in tools like GATK, Bioconductor, and utilizing public datasets (TCGA, cBioPortal).
- Strong understanding of statistics and ability to generate robust predictive models with multidimensional data.
- Strong interpersonal, verbal and written communication skills; proactive, self-motivated, adaptable.
- Demonstrated ability to translate complex data into clear biological insight and influence project direction.
Benefits
- Competitive cash compensation
- Robust equity awards
- Strong benefits
- Learning and development opportunities
Company overview
Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies for RAS-addicted cancers. The company is pioneering a new class of therapeutics that target oncogenic RAS mutations, which are among the most common drivers of human cancers. Revolution Medicines employs a unique approach to drug discovery, leveraging deep insights into RAS biology to develop small molecule inhibitors that can address previously undruggable targets. Their pipeline includes multiple clinical-stage candidates designed to inhibit various RAS pathway mutations, with a particular focus on KRAS G12C and other RAS variants. The company's scientific platform combines structural biology, medicinal chemistry, and computational approaches to design highly selective inhibitors. Revolution Medicines aims to transform cancer treatment by developing therapies that can overcome resistance mechanisms and provide durable clinical benefits for patients with RAS-driven malignancies. Their research represents a significant advancement in the field of targeted cancer therapy, addressing one of the most challenging areas in oncology drug development.