Principal Data Scientist – Healthcare AI / Google Cloud GenAI & Agentic Systems

About This Opportunity

CTI Staffing is partnering with a leading healthcare and life sciences organization to find a Principal Data Scientist for their AI team, based in Nashville, TN (hybrid, with onsite as needed).

This team is building production-grade generative AI and agentic AI solutions that turn complex clinical and operational data into safe, explainable decision support tools. The work spans clinical workflow automation, knowledge retrieval, and applied machine learning across structured and unstructured healthcare data. It's a client-facing, high-visibility role bridging clinical stakeholders, engineering teams, and executive leadership.

What You'll Do

• Lead the design of AI/ML solutions for healthcare use cases including clinical decision support, workflow automation, and knowledge retrieval

• Architect generative AI solutions using the Google Cloud AI ecosystem, including Vertex AI, Gemini, and RAG patterns

• Design and prototype agentic AI systems with human-in-the-loop oversight for clinical and operational workflows

• Build ML solutions for classification, prediction, summarization, and document intelligence across healthcare data

• Partner with stakeholders to assess data quality, terminology, and clinical workflow fit before scaling to production

• Define evaluation strategies for AI accuracy, bias, safety, drift, and explainability in a healthcare context

• Serve as senior technical advisor, translating data science concepts into business-aligned roadmaps for leadership

• Mentor data scientists and engineers while building reusable healthcare AI patterns and delivery playbooks

Requirements

What You Bring

Must-Have:

• 10+ years in data science, machine learning, or applied AI solution delivery, ideally in consulting or enterprise client environments

• Strong understanding of clinical workflows, healthcare operations, or life sciences data

• Hands-on experience with Google Cloud AI and data services, especially Vertex AI, Gemini, BigQuery, and Document AI

• Practical experience designing generative AI and agentic AI solutions, including prompt engineering, RAG architectures, and guardrails

• Strong foundation in supervised/unsupervised learning, NLP, model evaluation, and production ML lifecycle practices

• Understanding of healthcare data sensitivity, PHI protection, explainability, and AI governance

• Exceptional communication skills, able to translate technical and clinical complexity for executives and clinical leaders

• Experience mentoring data scientists or engineers on a consulting or delivery team

Nice-to-Have:

• Google Cloud Professional Machine Learning Engineer or Professional Data Engineer certification

• Databricks Machine Learning or TensorFlow certification

• HIPAA, clinical analytics, or Responsible AI/governance training

• Experience building reusable AI accelerators or delivery frameworks

• Background in payer/provider dynamics or clinical documentation systems

Technical Environment:

• Google Cloud Platform: Vertex AI, Gemini, BigQuery, Document AI

• Generative AI / Agentic AI orchestration, RAG architectures

• Python, ML/NLP frameworks, model evaluation tooling

What Success Looks Like:

• Client stakeholders trust and adopt the AI-driven decision support tools you design

• At least one GenAI or agentic use case moves from prototype to safe, monitored production

• Clinical and technical teams share an explainable framework for evaluating AI output quality and risk