Data Scientist

City of Hope

. Design, develop, and deploy advanced machine learning and artificial intelligence solutions supporting cancer research and clinical operations .

Posted 10/28/2026full-timeRemote • United StatesMid-LevelSenior💰 $53 - $85 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying advanced machine learning and artificial intelligence solutions, particularly in the context of cancer research and clinical operations. Proficient in integrating multimodal data and utilizing deep learning techniques, with a strong ability to communicate complex results to diverse audiences.

Highest-signal resume keywords

Machine Learning Model DevelopmentDeep Learning ExpertiseNatural Language Processing (NLP)Cloud Services ProficiencyData Visualization Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonDeep Neural NetworksSQL QueriesMachine Learning WorkflowsTransformer-Based ModelsGenerative AILarge Language Models (LLMs)Statistical ModelingVersion Control (Git)Data Science Techniques

Soft Skills

Creative Problem-SolvingIndependent WorkCollaborationCommunication Skills

Tools & Technologies

Microsoft AzureLangChainLangGraphEHR Systems

Industry Keywords

Cancer ResearchClinical OperationsMultimodal DataHealth Care EnvironmentPeer-Reviewed Publications

Tech Stack

Tools & technologies

AzureCloudPythonSQL

About the role

Key responsibilities & impact

Design, develop, and deploy advanced machine learning and artificial intelligence solutions supporting cancer research and clinical operations
Collaborate with administrative leaders, clinicians, and IT specialists
Query large datasets from multiple systems
Design, develop, validate, and deploy machine learning and deep learning models, including transformer-based architectures, multimodal neural networks, and LLM systems
Architect, deploy, and monitor production-grade AI systems, including LLM-based RAG pipelines, agent frameworks, and multimodal inference systems in cloud or distributed environments
Produce technical documentation, visualizations, and presentations
Lead technical design and implementation of complex AI initiatives involving research, clinical, and engineering teams
Complete work independently
Design multimodal AI solutions integrating text, imaging, genomic, and structured clinical data using deep learning and transformer-based models
Perform other related duties as assigned or requested

Requirements

What you’ll need

Master’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Applied Mathematics, Bioinformatics, Engineering, or a closely related quantitative field; or Bachelor’s degree with 3+ years of experience
Familiarity with a health care environment and EHR data
Familiarity with multimodal data such as genomics and medical images
Background in deep neural networks and Natural Language Processing (NLP)
Familiarity with cloud services platforms like Microsoft Azure
Experience with Generative AI and Large Language Models (LLMs), including RAG, fine-tuning, embedding models, prompt engineering, and integration into agentic data science workflows
Proficiency with version control systems (Git) and collaborative development workflows
Awareness of recent trends and developments in Data Science and Machine Learning
Experience with relational databases and SQL queries
Proficiency in Python and related data and ML packages
Proficiency in standard data science workflows, including training, evaluating/testing, and deploying machine learning and deep learning models
Familiarity with LLM frameworks and packages such as LangChain and LangGraph
Ability to work independently and use creative approaches to problem-solving
Ability to turn questions into testable hypotheses, extract data from complex databases, and create and evaluate statistical models
Experience in data visualization and communicating results to technical and non-technical audiences
Experience authoring and contributing to peer-reviewed scientific publications
Experience completing end-to-end projects with minimal to no supervision
Experience participating in large projects with many internal and external teams
Experience managing collaborative data science projects

Benefits

Comp & perks

Comprehensive Benefits (details provided via employer benefits link)