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

Tempus; Chicago (IL); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Benefits package

Job summary

Tempus is seeking a Senior Scientist, Applied Machine Learning and Generative AI, Pharma R&D to perform complex analyses and develop causal and agentic models. You will contribute to the Tempus platform for drug R&D, collaborating across research, engineering, and data science teams to deliver innovative computational solutions.

Ideal candidates possess strong applied ML, causal inference, and generative AI skills, with experience in LLMs, agentic systems, and foundation models in life

Qualifications

• Minimum PhD or Masters with 2+ years in industry or post‑doc.
• Strong background in causal AI, causal inference, and explainable AI.
• Experience with LLM‑driven agent architectures, prompt engineering, and RAG.

Responsibilities

• Advance Tempus platform for pharma R&D with ML and AI capabilities.
• Collaborate with Research, Engineering & Data Science teams across Tempus.
• Communicate complex results to diverse stakeholders.

Skills

Applied ML

Causal AI

Generative AI

Scientific communication

Education

PhD

MS + 2+ years

Tools

R

Python

SQL

LangChain

LangGraph

AutoGen

DSPy

Job description

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. The Senior Scientist, Applied Machine Learning and Generative AI, Pharma R&D will perform complex computational analyses and develop algorithms, causal models, and agent-based tools to advance the Tempus platform supporting drug R&D. The ideal candidate will possess strong applied machine learning, causal inference, and generative AI skills, with experience building and applying LLMs, agentic systems, causal frameworks, and foundation models in the life sciences. The candidate will also be proficient in communicating complex findings to various stakeholders.

Description:

Data Expertise: Tempus has one of the largest multimodal patient datasets ever collected, providing a unique opportunity to work with extensive and diverse data. Become an expert in Tempus' vast epidemiological, clinical, genomic, transcriptomic and pathology imaging data, along with the latest tools and techniques for their analysis and modeling.

Innovation: Drive continual improvement of the Tempus platform for pharmaceutical R&D by championing and building new machine learning and generative AI capabilities based on client needs and and industry trends.

Teamwork and collaboration: Work with Research, Engineering & Data Science teams across Tempus' expansive data science community to develop and deliver innovative computational solutions. Co-develop solutions with Pharma partner science and clinical teams

Drug R&D Expertise: Work with leading pharmaceutical companies. Gain proficiency in their strategies, drug modalities, and pipelines to identify where the Tempus platform can add value.

Scientific Communication: Skillfully navigate client interactions to extract and communicate the most impactful insights driving new R&D opportunities; effectively communicate complex technical results and methodologies to diverse external stakeholders.

Scientific Leadership & Influence: Empower computational biologists and RWE scientists through targeted AI guidance and hands on coaching to increase AI tool adoption to maximize impact.

Personal development: Continuously immerse yourself in the latest industry trends, best practices, and advancements in machine learning and AI to revolutionize drug R&D.

Qualifications:

Education and experience:

Minimum PhD (or Masters degree with 2+ years of relevant experience). Plus an additional 2+ years of relevant industry or post-doctoral experience.

Combining:

Quantitative and computational skills, with a focus on causal AI, causal inference, and/or explainable AI (e.g. Causal Machine Learning, Generative AI, Mathematics, biostatistics). Biological, medical, or drug development knowledge and data (e.g. oncology, RWE, medical science, or clinical drug development).

Technical/Scientific Skills:

Proficient in R, Python, and SQL, with specific expertise in frameworks for agentic orchestration (e.g., LangChain, LangGraph, AutoGen, or DSPy). Depp knowledge of machine learning and statistical modeling, with hands‑on experience in causal methodologies (e.g., Directed Acyclic Graphs, counterfactual reasoning, and heterogeneous treatment effect estimation). Applicable knowledge of LLM-driven agent architectures, including experience with prompt engineering, RAG (Retrieval-Augmented Generation), and function calling/tool use. Awareness of the uses of machine learning in molecular/biomedical data analysis or drug discovery/development. Experience working with molecular data, clinical trial and/or real‑world data and Track record of success: proven in peer reviewed publications.

Track record of success:

proven in peer reviewed publications.

Communication Skills:

Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences. Comfort in a client-facing role and ability to deliver technical training to both internal and external audiences.

Motivated:

Thrive in a fast‑paced environment and willing to shift priorities seamlessly.

Preferred Skillsets/Background:

Experience in integrative modeling of multi‑modal clinical and omics data. Strong understanding of data and artificial intelligence in drug R&D. Understanding of cancer biology. Previous experience working with large transcriptome and NGS data sets, or clinical or real‑world medical data.

#LI-DA1 CHI: $140,000-$200,000 NYC/SF: $150,000-$210,000 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.

Tempus was founded in August of 2015 by Eric Lefkofsky, after his wife was diagnosed with Breast Cancer. Shortly after he founded the company in an effort to bring the power of technology and artificial intelligence to cancer care, he convinced Ryan Fukushima to join as the company's first employee. Ryan and Eric began assembling a world class team, focused on building the first version of a platform capable of ingesting real time healthcare data in an effort to personalize diagnostics. We built the platform for oncology and have expanded it to neuropsychiatry, cardiology, infectious disease (through COVID), and radiology. Despite our rapid growth, our mission remains the same—to help make sure patients are on the right drug at the right time, so they can live longer and healthier lives. We're looking for people who can change the world. Who question the status quo and don't shy away from tough problems. For the builders who are never done building and the learners who are never done learning. We're looking for passionate people with undying curiosity. Those who want to attack one of the most challenging problems mankind has ever faced. Head on.