Scientist II, Computational Biology, Pharma R&D

Tempus AI; Boston (MA); Presencial; USD 90 000 - 150 000; Tempo integral

Resumo da oferta

Tempus AI seeks a Scientist II to join our Computational Biology, Pharma R&D team. The role focuses on integrating large-scale molecular and clinical datasets to generate actionable insights for drug discovery and translational science, and building next-generation tools that enhance impact and efficiency.

The successful candidate will combine strong computational and statistical skills with biology expertise, engaging with external stakeholders and leveraging AI (foundation models, LLMs) to

Qualificações

• PhD or equivalent with computational biology focus.
• Proficiency in R and/or Python for bioinformatics and data analysis.
• Experience with large-scale biological datasets and translational science.

Responsabilidades

• Pharma collaboration & strategy: partner with collaborators to address questions in target discovery and biomarker development.
• Computational analysis: integrate genomic, transcriptomic, imaging, and clinical data; apply stats and ML methods.
• AI & LLM innovation: use LLMs and agentic workflows to accelerate research tasks.
• Method development: implement new methods for real-world and omics data analysis.
• Cross-functional collaboration: work with Research, Clinical, Data Science, and Engineering teams.
• Scientific communication: present results to technical and non-technical stakeholders.

Conhecimentos

Machine Learning

Statistical analysis

Cancer biology knowledge

Big data analysis

Communication skills

LLM-based coding assistants usage

Formação académica

PhD in Computational Biology/ Bioinformatics/ Biostatistics/ ML or related field

Master’s degree with 3+ years of relevant experience

Ferramentas

R

Python

SQL

Descrição da oferta de emprego

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

We are seeking a Scientist II to join our Computational Biology, Pharma R&D team. We work at the intersection of biological data science and AI to support collaborations with major pharmaceutical partners. 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 the impact and efficiency of our work.

The successful candidate will combine strong computational and statistical skills with a deep interest in biology and translational science. They will be comfortable working with real-world data, engaging with external scientific stakeholders, and leveraging AI (foundation models, Large Language Models, agentic systems, etc.) to scale tasks and augment insights.

Key Responsibilities

• Pharma Collaboration & Strategy: 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.
• Computational Analysis & Insight Generation: 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.
• AI & LLM Innovation: 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.
• Method Development and Platform Contribution: 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.
• Cross-Functional Collaboration: Work closely with colleagues in Research, Clinical, Data Science, and Engineering to refine analyses and build scalable solutions.
• 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.

Qualifications

• Education: PhD in Computational Biology, Bioinformatics, Biostatistics, Machine Learning, or a related field (or master’s degree with 3+ years of relevant experience).
• Technical Proficiency: 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.
• Scientific Knowledge: Strong understanding of cancer biology, immunology, or human disease mechanisms.
• Data Expertise: Demonstrated experience analyzing large-scale biological datasets (e.g., NGS, RNA-seq, other genomics or transcriptomics data), ideally in oncology, immunology, or human disease.
• Soft Skills: Excellent written and verbal communication skills with comfort in client-facing roles. Ability to thrive in a fast-paced, dynamic environment.

Preferred Skillsets

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

CHI: $90,000-$135,000

NYC: $100,000-$150,000

The expected salary range may vary for other locations. Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.