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Salary: USD 100,000 - 175,000 / annual
Tempus is seeking a Senior Scientist II in Computational Biology to join the Pharma R&D team. This role sits at the intersection of biological data science and AI, supporting high-impact collaborations with major pharmaceutical partners. You will work with large-scale molecular and clinical datasets to generate actionable insights for drug discovery and development.
Key responsibilities include:
• Pharma Collaboration & Strategy: Partner with pharmaceutical collaborators on target discovery, biomarker development, and clinical development. Translate partner needs into technical requirements and design analytical plans leveraging Tempus's multimodal platform.
• Computational Analysis & Insight Generation: Execute robust analyses integrating genomic, transcriptomic, imaging, and clinical data. Apply statistical and computational best practices to derive insights related to clinical trial design, patient selection, treatment response, and disease biology.
• AI & LLM Innovation: Incorporate LLMs and AI tools into workflows to automate code development, discovery, and documentation. Design and prototype agentic workflows integrating foundation models for new insights and predictive models.
• Method Development and Platform Contribution: Evaluate and implement new methods for analyzing real-world, clinical, and 'omic datasets (survival analysis, causal inference, multi-modal integration). Contribute to reusable code, internal packages, and best practices.
• Cross-Functional Collaboration: Work with Research, Clinical, Data Science, and Engineering teams to refine analyses, build scalable solutions, and align efforts with platform roadmaps.
• Scientific Communication: Communicate complex methods and results to technical and non-technical stakeholders. Prepare internal reports, external deliverables, and manuscripts demonstrating impact.
• Leadership: Demonstrate project-level leadership ensuring high-quality results. Set priorities, coordinate resources, mentor junior scientists, and maintain excellence in execution.
Qualifications:
• Education: PhD in Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or related field (or Master's degree with 4+ years relevant experience), plus 2+ years industry or post-doctoral experience.
• Technical Proficiency: Proficiency in R and/or Python with computational biology and scientific computing libraries. Experience with machine learning, LLM-based coding assistants (Copilot, Cursor), and agentic frameworks. Strong software engineering practices (version control, modular code, documentation). Strong statistics and data analysis grounding, including study design and real-world clinical data interpretation. Quality code review and QA/QC capabilities.
• Scientific Knowledge: Strong understanding of cancer biology, immunology, or human disease mechanisms with ability to interpret and summarize findings.
• Data Expertise: Demonstrated experience analyzing large-scale biological datasets (NGS, RNA-seq, genomics, transcriptomics), ideally in oncology, immunology, or human disease.
• Scientific Leadership: Demonstrated project leadership and people mentorship.
• Soft Skills: Excellent written and verbal communication with comfort in client-facing roles. Strong collaborator. Ability to thrive in fast-paced, dynamic settings.
Preferred: Practical experience with generative AI and LLM configuration; expertise in RWE, survival analysis, causal inference, network/systems biology, or multi-modal integration; strong publication record; drug development lifecycle understanding; SQL and large relational database experience.
