Senior Scientist, Computational Biology, Pharma R&D

Senior Scientist, Computational Biology, Pharma R&D

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We are seeking an experienced Senior Scientist to join the Computational Biology, Pharma R&D team. This group operates at the intersection of biological data science and AI, supporting high‑impact collaborations with major pharmaceutical partners. The ideal candidate will demonstrate strong scientific leadership, deep expertise in computational biology and AI tools, and a proven track record of success. The role focuses on integrating large‑scale molecular and clinical datasets, generating actionable insights for drug discovery and development, and building next‑generation research tools that enhance impact and efficiency.

• Pharma Collaboration & Strategy:
  Partner with pharmaceutical collaborators in target discovery, biomarker development, and clinical development teams. Understand their scientific and clinical objectives, pipelines, and drug modalities. Translate partner needs into key questions and technical requirements to design analytical plans that leverage the Tempus multimodal platform.
• Computational Analysis & Insight Generation:
  Execute robust, reproducible analyses integrating genomic, transcriptomic, imaging, and clinical data. Apply appropriate statistical and computational best practices to derive insights related to clinical trial design, patient selection, treatment response, resistance mechanisms, and disease biology.
• AI & LLM Innovation:
  Incorporate LLMs and other AI tools into day‑to‑day workflows to automate, streamline and accelerate code development, discovery, documentation, and review. Design and prototype agentic workflows integrating foundation models and LLMs to power new insights and predictive models.
• Method Development and Platform Contribution:
  Evaluate, adapt, and implement new methods for the analysis of real‑world, clinical, and ’omic datasets (e.g., survival analysis, causal inference, multi‑modal integration). Contribute to reusable code, internal packages, and best practices that can be applied across multiple collaborations and programs.
• Cross‑Functional
  
  Collaboration:
  
  Work closely with colleagues in Research, Clinical, Data Science, and Engineering to refine analyses, build scalable solutions, and align scientific efforts with platform and product roadmaps.
• Scientific Communication:
  Communicate complex methods and results clearly to both technical and non‑technical stakeholders. Prepare and present internal reports, external‑facing deliverables, and, where appropriate, manuscripts or conference materials that demonstrate the impact of Tempus data and technologies on partner programs.
• Leadership:
  Demonstrate strong project‑level leadership to ensure delivery of high‑quality results efficiently and effectively. Set clear priorities, coordinate resources, and proactively identify and address obstacles to meet project milestones and deadlines. Mentor junior scientists and uphold a standard of excellence in project execution.

• Education:
  • PhD in Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related field (or Masters degree with 3+ years of relevant experience).
  • Plus an additional 2+ years of relevant industry or post‑doctoral experience.
• Track record of success:
  Proven in peer‑reviewed publications.
• Technical Proficiency:
  • Proficiency in R and/or Python, including experience with common computational biology and scientific computing libraries.
  • Proficiency applying machine learning, LLM‑based coding assistants (e.g., Copilot, Cursor) and agentic frameworks for biological/clinical research.
  • Adherence to good software engineering practices (version control, modular code, documentation).
  • Experience working with SQL and large relational databases.
  • Strong grounding in statistics and data analysis, including study design considerations and interpretation of real‑world clinical data.
  • Proficiency in providing quality code review and QA/QC for the work of others.
• Scientific Knowledge:
  Strong understanding of cancer biology, immunology, or human disease mechanisms, with…