Revolution Medicines
Targeting RAS-addicted cancers with next-generation precision oncology
About Revolution Medicines
Funding & Growth
✓ Pros
- • Compelling RAS oncology science with best-in-class pipeline (RMC-6236, RMC-9805)
- • Competitive compensation with published salary bands
- • Hybrid work model at Redwood City HQ
- • Strong clinical-stage momentum — multiple programs in Phase 1/2
- • Collaborative culture bridging computational and clinical teams
✗ Cons
- • Clinical-stage risk — pipeline still in Phase 1/2
- • Redwood City location (limited remote options for most roles)
- • Biostatistics and clinical data science focus — fewer pure ML/AI roles than TechBio peers
- • Smaller computational biology team relative to large pharma
🏢 Working Here
Revolution Medicines is a clinical-stage precision oncology company in Redwood City, CA, focused exclusively on RAS-addicted cancers — a notoriously difficult target class that includes KRAS-mutant pancreatic, lung, and colorectal cancers.
The company pioneered RAS(ON) inhibitors that target the active GTP-bound form of RAS, setting it apart from earlier KRASG12C(OFF) inhibitors like sotorasib and adagrasib.
With multiple programs in the clinic (RMC-6236, RMC-9805, RMC-6291) and a public listing on Nasdaq (RVMD), RevMed offers the scientific focus of a biotech startup with the resources and process rigor of a company approaching late-phase trials.
The data science organization spans biostatistics, statistical programming, exploratory data science, and clinical data management — all supporting a pipeline that is advancing rapidly toward potential registration.
🧬 Bioinformatics Focus
Computational work at Revolution Medicines centers on clinical-stage biostatistics and data science rather than early discovery.
Roles include statisticians designing and analyzing oncology trials (early and late phase), statistical programmers building CDISC-compliant SDTM/ADaM datasets and regulatory submissions, exploratory data scientists applying ML and causal inference to clinical trial and real-world data, and clinical data managers overseeing EDC and data quality.
The company is building out more advanced modeling capabilities — survival analysis, Bayesian methods, causal inference, HEOR — as its pipeline matures toward registration-enabling studies.
Strong SAS and R skills are essential; Python and ML experience are valued for the Exploratory Data Science group.
📈 Career Growth & Development
Career Paths
Biostatistics Track
Statistical Programming Track
Data Science Track
Compensation
Published salary bands: Associate Director $186K–$233K, Director $211K–$264K, Senior Director $244K–$305K. RSUs and annual bonuses included.
Pipeline Momentum
Multiple programs advancing rapidly — early hires can grow into regulatory-submission leadership roles faster than at large pharma.
Science
Work directly on RAS(ON) programs addressing the most common oncogenic mutations (KRASG12D, G12C) in pancreatic, lung, and colorectal cancer.
Cross-functional Exposure
Strong collaboration across clinical development, medical affairs, and regulatory — broad visibility for quantitative scientists.