Scientist II, Computational Biology, Pharma R&D

Tempus AI•Boston, MA

2d•$90,000 - $150,000

About The Position

Tempus is seeking a Scientist II to join their Computational Biology, Pharma R&D team. This role operates at the intersection of biological data science and AI, supporting collaborations with major pharmaceutical partners. The position focuses on integrating large-scale molecular and clinical datasets, generating actionable insights for drug discovery and development, and building next-generation research tools. The ideal candidate will possess strong computational and statistical skills, a deep interest in biology and translational science, and experience with real-world data, external scientific stakeholders, and leveraging AI technologies like foundation models, Large Language Models, and agentic systems.

Requirements

PhD in Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related field (or master’s degree with 3+ years of relevant experience).
Proficiency in R and/or Python, including experience with common computational biology and scientific computing libraries.
Proficiency in using machine learning, LLM-based coding assistants (e.g., Claude Code, Codex), 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.
Strong understanding of cancer biology, immunology, or human disease mechanisms.
Demonstrated experience analyzing large-scale biological datasets (e.g., NGS, RNA-seq, other genomics or transcriptomics data), ideally in oncology, immunology, or human disease.
Excellent written and verbal communication skills with comfort in client-facing roles.
Ability to thrive in a fast-paced, dynamic environment.

Nice To Haves

Practical experience configuring or adapting LLMs, or using related tools/frameworks, to support scientific work.
Expertise in one or more of the following: Real-world evidence (RWE), survival analysis, causal inference, network/systems biology, or multimodal integration.
A strong history of peer-reviewed publications or conference presentations.
Understanding of the drug development lifecycle, from target discovery to clinical development.

Responsibilities

Partner with pharmaceutical collaborators to execute computational research plans that leverage the Tempus multimodal platform to address key questions in target discovery, biomarker development, and clinical development.
Perform robust, reproducible analyses integrating genomic, transcriptomic, imaging, and clinical data. Apply appropriate statistical and computational methods to derive insights related to clinical trial design, patient selection, treatment response, resistance mechanisms, and disease biology.
Incorporate LLMs, agentic workflows, foundation models and other AI tools into day-to-day workflows to accelerate code development, discovery, documentation, review, and insight generation.
Evaluate, adapt, and implement new methods for the analysis of real-world, clinical, and omics datasets (e.g., survival analysis, causal inference, multimodal integration). Contribute to reusable code, internal packages, and best practices that can be applied across multiple collaborations and programs.
Work closely with colleagues in Research, Clinical, Data Science, and Engineering to refine analyses and build scalable solutions.
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.