Compensation Overview

Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies to inhibit frontier targets in RAS-addicted cancers.  The company’s R&D pipeline comprises RAS(ON) Inhibitors designed to suppress diverse oncogenic variants of RAS proteins, and RAS Companion Inhibitors for use in combination treatment strategies. As a new member of the Revolution Medicines team, you will join other outstanding professionals in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway.

The Opportunity:

In this role, you will work within our Translational Medicine group transferring, organizing, curating and disseminating biomarker data from clinical trial samples. This incoming data consists of a diverse mix of next-generation sequencing, downstream variant calls, imaging, and other molecular assay outputs. The bioinformatics data engineer will work on various projects in different phases of drug development and contribute to the cross-functional bioinformatics team which includes other bioinformaticians and data scientists. As a Bioinformatics Data Engineerin Translational Medicine, you will:

• Act as a main liaison between internal scientists and external molecular diagnostic providers.

• Be the primary point of contact for the data transfer process, establishing connections between our cloud storage and external file shares.

• Help develop scripts and processes to clean, upload and accession biomarker data from clinical trails into internal systems for further analysis.

• Carry out data modeling and curation to ensure data quality and relevance.

• Collaborate with other departments to share and disseminate data in a controlled and documented manner.

• Develop web-based data visualization dashboards using python and R frameworks.

• Use and modify data analysis pipelines using nextflow and WDL.     

Required Experience, Skills, and Education:

• Master’s or bachelor’s degree with 3+ years’ experience in biology/computer science related field.

• Expertise using linux clusters, cloud computing and file systems.

• Proficient in designing and querying databases using SQL and object-relational mapping techniques.

• Skilled in utilizing Python and R for data manipulation and analysis.

• Strong familiarity with bioinformatics data types and outputs.

• Excellent communication skills, enabling effective collaboration and conveying technical information clearly to diverse audiences.

Preferred Skills:

• Experience using visualization packages such as R Shiny, PowerBI or similar systems.

• Experience in biomarker data analysis and bioinformatics.

• Familiarity with large genomic data sets (GDC, TCGA, etc.).

• Experience in tools to analyze cancer genomics datasets (GATK, Salmon, OncoKB, VEP, etc.).

• Development experience in groups using IDE’s, a ticketing system and software control systems (GIT).

The expected salary range for this role is $120,000 to $145,000. An individual’s position within the range may be influenced by multiple factors, including skills and experience in role, overall performance, individual impact and contributions, tenure, and market dynamics. Base salary is one part of the overall total rewards program at RevMed, which includes competitive cash compensation, robust equity awards, strong benefits, and significant learning and development opportunities.

Revolution Medicines is an equal opportunity employer and prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, disability, marital status, medical condition, and veteran status.

Revolution Medicines takes protection and security of personal data very seriously and respects your right to privacy while using our website and when contacting us by email or phone. We will only collect, process and use any personal data that you provide to us in accordance with our CCPA Notice and Privacy Policy. For additional information, please contact [email protected].

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