Senior Scientist I, Applied Machine Learning, Generative AI

Tempus AI

. Perform complex computational analyses .

Posted 9/30/2026full-timeUnited StatesSenior💰 $140,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in computational analyses, causal AI, and machine learning applications in drug R&D, with proficiency in R, Python, and SQL. Capable of communicating complex methodologies and insights effectively to diverse stakeholders while empowering teams through training and collaboration.

Highest-signal resume keywords

PhD Or Master's DegreeCausal AI And Causal InferenceProficiency In R, Python, And SQLExpertise In Agentic Orchestration FrameworksExperience With Molecular Data And Clinical Trial Data

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Computational AnalysisAlgorithm DevelopmentMachine LearningStatistical ModelingCausal MethodologiesDirected Acyclic GraphsCounterfactual ReasoningHeterogeneous Treatment Effect EstimationPrompt EngineeringIntegrative Modeling

Soft Skills

Excellent Communication SkillsClient-Facing Role ComfortTechnical Training DeliveryPersuasive Presentation Skills

Tools & Technologies

LangChainLangGraphAutoGenDSPyLarge Language ModelsReal-World Evidence Tools

Industry Keywords

Drug R&DEpidemiological DataGenomic DataTranscriptomic DataPathology Imaging DataCancer BiologyBiomedical Data Analysis

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Perform complex computational analyses
Develop algorithms, causal models, and agent-based tools supporting drug R&D
Become an expert in Tempus’ epidemiological, clinical, genomic, transcriptomic, and pathology imaging data
Drive continual improvement of the Tempus platform for pharmaceutical R&D by building machine learning and generative AI capabilities
Work with Research, Engineering, and Data Science teams to develop and deliver computational solutions
Co-develop solutions with pharmaceutical partner science and clinical teams
Work with pharmaceutical companies to understand strategies, drug modalities, and pipelines and identify opportunities for the Tempus platform
Extract and communicate impactful insights driving new R&D opportunities
Communicate complex technical results and methodologies to diverse external stakeholders
Empower computational biologists and RWE scientists through AI guidance and hands-on coaching
Stay current with industry trends, best practices, and advancements in machine learning and AI

Requirements

What you’ll need

Minimum PhD, or Master's degree with 2+ years of relevant experience
Plus an additional 2+ years of relevant industry or post-doctoral experience
Quantitative and computational skills focused on causal AI, causal inference, and/or explainable AI
Biological, medical, or drug development knowledge and data
Proficiency in R, Python, and SQL
Expertise in agentic orchestration frameworks such as LangChain, LangGraph, AutoGen, or DSPy
Deep knowledge of machine learning and statistical modeling
Hands-on experience with causal methodologies, including Directed Acyclic Graphs, counterfactual reasoning, and heterogeneous treatment effect estimation
Knowledge of LLM-driven agent architectures, prompt engineering, RAG, and function calling/tool use
Awareness of machine learning applications in molecular/biomedical data analysis or drug discovery/development
Experience with molecular data, clinical trial data, and/or real-world data
Proven success in peer-reviewed publications
Excellent written and verbal communication skills
Ability to present complex information clearly and persuasively to diverse audiences
Comfort in a client-facing role
Ability to deliver technical training to internal and external audiences
Experience in integrative modeling of multimodal clinical and omics data preferred
Strong understanding of data and artificial intelligence in drug R&D preferred
Understanding of cancer biology preferred
Experience with large transcriptome and NGS datasets, or clinical or real-world medical data preferred

Benefits

Comp & perks

Incentive compensation may be offered
Restricted stock units may be offered
Medical and other benefits may be offered depending on the position