Cardinal Health · 14 hours ago
Senior Data Scientist, Navista
United States
Full-time
Remote
Senior Level, Lead/Staff
$123K/yr - $176K/yr
8+ years expCardinal Health is committed to empowering community oncology practices with patient-centered care through its Navista division. They are seeking a Senior Data Scientist to lead the development of advanced AI solutions, particularly in Generative AI and Large Language Models, to enhance their oncology application suite and support clinical decision-making.
Health CareHospitalMedical
Responsibilities
Research & Development: Lead the research, design, and development of novel Generative AI models and algorithms, including but not limited to LLMs, diffusion models, GANs, and VAEs, to address complex business challenges
LLM Expertise: Architect, fine-tune, and deploy Large Language Models for various applications such as natural language understanding, generation, summarization, question-answering, and code generation, with a focus on extracting insights from unstructured clinical and research data
Agentic Systems Design: Design and implement intelligent agentic systems capable of autonomous decision-making, planning, reasoning, and interaction within complex environments, leveraging LLMs as core components
Predictive Modeling: Develop and deploy advanced predictive models and capabilities using both structured and unstructured data, particularly within the oncology space, to forecast outcomes, identify trends, and support clinical or commercial decision-making
Prompt Engineering & Optimization: Develop advanced prompt engineering strategies and techniques to maximize the performance and reliability of LLM-based applications
Data Strategy for GenAI: Work with data engineers to define and implement data collection, preprocessing, and augmentation strategies specifically tailored for training and fine-tuning generative models and LLMs, including techniques for handling and enriching unstructured oncology data (e.g., clinical notes, pathology reports)
Model Evaluation & Deployment: Develop robust evaluation metrics and methodologies for generative models, agentic systems, and predictive models. Oversee the deployment, monitoring, and continuous improvement of these models in production environments
Collaboration & Leadership: Collaborate closely with machine learning engineers, software engineers, and product managers to integrate AI solutions into our products. Provide technical leadership and mentorship to junior data scientists
Innovation & Thought Leadership: Stay abreast of the latest advancements in GenAI, LLMs, and agentic AI research. Proactively identify new opportunities and technologies that can enhance our capabilities and competitive advantage
Ethical AI: Ensure the responsible and ethical development and deployment of AI systems, addressing potential biases, fairness, and transparency concerns
Qualification
Required
8-12 years of experience as a Data Scientist or Machine Learning Engineer, with a significant focus on deep learning and natural language processing
Proven hands-on experience with Generative AI models (e.g., Transformers, GANs, VAEs, Diffusion Models) and their applications
Extensive experience working with Large Language Models (LLMs), including fine-tuning, prompt engineering, RAG (Retrieval Augmented Generation), and understanding various architectures (e.g., GPT, Llama, BERT, T5)
Demonstrated experience in designing, building, and deploying agentic systems or multi-agent systems, including concepts like planning, reasoning, and tool use
Strong experience working with unstructured data, particularly in the oncology domain (e.g., clinical notes, pathology reports, genomic data, imaging reports), and extracting meaningful features for analysis
Demonstrated ability to create and deploy predictive capabilities and models from complex datasets, including those with unstructured components
Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
Experience with relevant libraries and tools (e.g., Hugging Face Transformers, LangChain, LlamaIndex)
Strong understanding of machine learning fundamentals, statistical modeling, and experimental design
Experience with at least one cloud platforms (GCP, Azure) for training and deploying large-scale AI models
Excellent problem-solving skills, with the ability to tackle complex, ambiguous problems and drive solutions
Strong communication and presentation skills, capable of explaining complex concepts
Preferred
Bachelor's degree in related field, or equivalent work experience
Experience in the healthcare or life sciences industry, specifically with oncology data and research
Experience with MLOps practices for deploying and managing large-scale AI models
Familiarity with distributed computing frameworks (e.g., Spark, Dask)
Experience contributing to open-source AI projects
Benefits
Medical, dental and vision coverage
Paid time off plan
Health savings account (HSA)
401k savings plan
Access to wages before pay day with myFlexPay
Flexible spending accounts (FSAs)
Short- and long-term disability coverage
Work-Life resources
Paid parental leave
Healthy lifestyle programs
Company
Cardinal Health
Cardinal Health is a manufacturer and distributor of medical and laboratory products.
10001+ employees
H1B Sponsorship
Cardinal Health has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (128)
2024 (116)
2023 (140)
2022 (158)
2021 (106)
2020 (142)
Funding
Current Stage
Public CompanyTotal Funding
$1.08B2025-08-28Post Ipo Debt· $1B
2006-08-16Post Ipo Debt· $78M
1983-08-12IPO
Leadership Team
Aaron Alt
Chief Financial Officer
T
Tony Caprio
Executive Vice President
Recent News
Morningstar.com
2026-01-16
Company data provided by crunchbase