Overview In this role you drive research programs with top biopharma partners, applying computational methods to oncology and precision medicine. You will translate complex findings for external stakeholders and integrate multi-modal data to inform trial design, patient selection, and treatment strategies. You'll work with cross-functional teams to advance the Tempus platform's impact in cancer care, leveraging AI and real-world evidence to accelerate research and collaboration with industry leaders. This is a hands-on, client-facing scientific leadership role with a strong emphasis on delivering actionable insights at scale.
Compensation / Benefits- full range of benefits
- incentive compensation
- restricted stock units
- medical benefits
Responsibilities- Lead scientific communication with external stakeholders, presenting technical results clearly
- Perform robust computational analyses integrating genomic, transcriptomic, imaging, and clinical data
- Apply statistical and computational methods to inform clinical trial design, patient selection, and understanding resistance mechanisms
- Incorporate LLMs and AI tools into workflows to accelerate development and insight generation
- Collaborate with Research, Engineering & Data Science teams to deliver innovative solutions
- Partner with big pharma to understand client strategies and identify where Tempus adds value
- Stay current with industry trends and apply knowledge to improve research quality
Key requirements- PhD with 4+ years of experience or Master with 6+ years of experience
- Quantitative and computational skills in Computational Biology, Biostatistics/Statistical Genetics, Machine Learning, or Bioinformatics
- Biological or medical knowledge in Oncology, Immunology, or Human Disease
- Genomics and transcriptomics expertise
- Experience with target, drug, or diagnostic discovery or clinical development
- Proficiency in R, Python, and SQL with relevant computational biology packages
- Strong understanding of cancer biology and a track record of peer-reviewed publications
- Knowledge of machine learning and statistical modeling
- Excellent written and verbal communication for diverse audiences
- Client-facing experience and ability to navigate external stakeholders
- Motivated and adaptable in a dynamic environment
- Strong communication and presentation skills
- Collaborative and cross-functional mindset
- R, Python, SQL
- Pandas, Jupyter Notebook
- tidyverse, Git, matplotlib
