Senior Scientist, Computational Biology, Life Science Strategy (AI)

Location: Chicago, United States; other listed locations include Boston, Redwood City, and New York City.

Salary: $100,000–$160,000 for Chicago; $115,000–$175,000 for New York City/San Francisco. The range may vary for Colorado, Illinois, and New York.

Company

Tempus advances precision medicine through artificial intelligence and large-scale clinical and molecular data to improve patient outcomes and accelerate drug development.

What you will do

• Partner with life science strategy, market intelligence, pharma R&D, and other stakeholders to develop analysis plans and deliver data insights on biomarkers and clinical development.
• Perform reproducible analyses integrating genomic, transcriptomic, imaging, and clinical data for trial design, patient selection, treatment response, resistance mechanisms, and disease biology.
• Use LLMs and AI tools to accelerate coding, discovery, documentation, and review; prototype agentic workflows and predictive models.
• Evaluate and implement methods such as survival analysis, causal inference, and multi-modal integration, contributing reusable code, packages, and best practices.
• Collaborate with Research, Clinical, Data Science, and Engineering to build scalable solutions aligned with platform and product roadmaps.
• Lead projects, coordinate resources, mentor junior scientists, communicate findings, and prepare reports, deliverables, manuscripts, or conference materials.

Requirements

• PhD in Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related field, or a master’s degree with 3+ years of relevant experience, plus 2+ additional years of relevant industry or post-doctoral experience.
• Proficiency in R and/or Python with computational biology and scientific computing libraries.
• Experience applying machine learning, LLM-based coding assistants, and agentic frameworks to biological or clinical research.
• Good software engineering practices, including version control, modular code, documentation, code review, and QA/QC.
• Experience with SQL and large relational databases, plus strong statistics, data analysis, study design, and interpretation of real-world clinical data.
• Strong understanding of cancer biology, immunology, or human disease mechanisms and experience analyzing large-scale biological datasets such as NGS, RNA-seq, genomics, or transcriptomics data.
• Proven peer-reviewed publication record, project leadership, people mentorship, excellent written and verbal communication, and comfort in client-facing roles.
• Ability to collaborate and thrive in a fast-paced, dynamic setting.

Nice to have

• Experience configuring or adapting LLMs and related tools or frameworks for scientific work.
• Expertise in real-world evidence, survival analysis, causal inference, network or systems biology, or multi-modal integration.
• Strong history of peer-reviewed publications or conference presentations.
• Understanding of the drug development lifecycle from target discovery through clinical development.

Culture & Benefits

• Full-time role supporting collaborations across Research, Clinical, Data Science, Engineering, and pharmaceutical partners.
• Benefits may include incentive compensation, restricted stock units, medical benefits, and other benefits depending on the position.
• Equal opportunity employment with consideration of qualified applicants with arrest or conviction records in accordance with applicable law.