Senior Scientist I, Applied Machine Learning and Generative AI, Pharma R&D

What you'll do

• Build and improve machine learning, generative AI, causal modeling, and agent-based capabilities for pharmaceutical R&D.
• Collaborate with Tempus teams and pharmaceutical partners to develop solutions and communicate scientific findings to stakeholders.
• Coach computational biology and real-world evidence scientists on AI tools and adoption.

What they ask for

• PhD, or a master’s degree with 2+ years of relevant experience, plus an additional 2+ years of relevant industry or postdoctoral experience.
• Quantitative/computational skills in causal AI, causal inference, or explainable AI, along with biological, medical, or drug-development knowledge.
• Proficiency in R, Python, and SQL; machine learning and statistical modeling expertise, including hands-on causal methods.
• Experience with LLM-driven agent architectures, prompt engineering, RAG, and function calling/tool use; peer-reviewed publications.

Nice to have

• Integrative modeling of multimodal clinical and omics data.
• Understanding of cancer biology and experience with transcriptome, NGS, clinical, or real-world medical data.

Pay

$140,000-$200,000 USD base salary; $150,000-$210,000 USD base salary

Tools

R, Python, SQL, LangChain, LangGraph, AutoGen, DSPy

AI focus

Develops and applies machine learning, causal AI, generative AI, LLM agents, and foundation models for pharmaceutical R&D.