Senior Computational Biologist I

Tempus AI Tempus AI · Vertical AI · New York City, Chicago

Seeking a Senior Computational Biologist to analyze large-scale, multi-omic molecular and real-world clinical datasets for precision medicine research. This role supports the Discover Data Science team, translating scientific questions into actionable insights for patient care and enhancing research capabilities.

What you'd actually do

  1. Lead and contribute to research projects in support of research initiatives within R&D and Medical Affairs, leveraging large-scale real-world clinical and multi-omic molecular data.
  2. Present insights from research studies to external research partners through formal presentations and communicate research findings effectively.
  3. Stay updated on methodological advancements in real-world studies, next generation sequencing (DNA/RNA) and oncology guidelines.
  4. Communicate analytical results, and scientific findings clearly to audiences with varying levels of technical and genomics expertise.
  5. Participate in publications and podium activities.

Skills

Required

  • R
  • SQL
  • genomic data analysis
  • multi-omic data analysis
  • real-world clinical data analysis
  • project management
  • collaboration

Nice to have

  • integrating molecular data with real-world evidence
  • AWS
  • Bigquery
  • Google Cloud Platform (GCP)
  • machine learning techniques
  • predictive and prognostic algorithms in medical research

What the JD emphasized

  • strong background in analyzing large-scale, multi-omic molecular and real-world clinical datasets
  • PhD degree in quantitative NGS-related disciplines (e.g. Computational Biology, Genetics, or similar). Alternatively, a PhD in computational biology with a strong record of multi-omic, high-throughput sequencing data analysis
  • Experience deriving oncology-specific clinical insights using genomic data and deriving real-world endpoints using time-to-event methodologies within a retrospective database.
  • proven ability to collaborate with teams of multi-disciplinary scientists to define and execute analysis plans to address scientific questions using omics datasets (genomics, transcriptomics).

Other signals

  • large-scale, multi-omic molecular and real-world clinical datasets
  • translate their scientific questions into insight generation
  • enhance Tempus’ research capabilities