Principal Data Scientist

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.  

As a Principal Data Scientist (SG29) within Optum Rx, you will serve as a senior individual contributor, technical architect, and hands-on leader responsible for designing, building, and productionizing advanced AI solutions across Generative AI, Agentic AI, and Classical AI/ML domains.

You will partner closely with business leaders, product teams, engineering teams, and platform organizations to solve complex healthcare and pharmacy benefit management challenges using cutting-edge AI technologies. This role requires deep expertise in machine learning, large language models (LLMs), agentic systems, and data science, combined with strong architecture and delivery leadership capabilities.

The ideal candidate brings a proven track record of translating business challenges into scalable, secure, compliant, and production-ready AI solutions that deliver measurable business impact across pharmacy operations, clinical programs, member engagement, provider enablement, cost optimization, and healthcare outcomes.

Primary Responsibilities:

• AI Strategy, Architecture & Technical Leadership
  • Lead architecture, design, and implementation of enterprise-scale AI solutions across Generative AI, Agentic AI, machine learning, and advanced analytics domains
  • Define technical vision, architecture standards, reusable frameworks, and best practices for AI-driven products and platforms within Optum Rx
  • Serve as the technical authority for AI solution design, balancing business objectives with scalability, reliability, security, governance, and cost considerations
  • Establish reference architectures, design patterns, reusable components, and deployment frameworks to accelerate AI adoption across teams
  • Drive technology evaluations, proof-of-concepts, and innovation initiatives leveraging emerging AI technologies and frameworks
• Generative AI & Agentic AI Development
  • Design, build, and productionize Agentic AI systems capable of multi-step planning, reasoning, tool utilization, validation, and autonomous workflow execution within defined governance guardrails
  • Develop enterprise GenAI solutions leveraging approved foundation models, including Claude, OpenAI GPT/Codex, and equivalent enterprise LLM platforms
  • Build intelligent assistants and copilots for:
    • Data exploration and analytics
    • Pharmacy and healthcare operations
    • Engineering productivity
    • Knowledge management
    • Workflow automation
    • Clinical and business decision support
    • Implement advanced Retrieval-Augmented Generation (RAG), Graph RAG, agent orchestration, memory management, tool-calling, and AI workflow patterns
    • Design AI systems that combine LLMs, knowledge graphs, search technologies, business rules, and predictive models to improve accuracy and trustworthiness
    • Establish evaluation frameworks for LLM quality, hallucination reduction, safety, latency, and cost optimization
• Classical AI, Machine Learning & Advanced Analytics
  • Lead development of predictive, prescriptive, and optimization models addressing key healthcare and pharmacy business challenges
  • Apply advanced statistical modeling, machine learning, deep learning, NLP, computer vision, speech technologies, and reinforcement learning where appropriate
  • Build hybrid AI systems that integrate traditional ML models with Generative AI and Agentic AI capabilities
  • Design experimentation frameworks, model evaluation methodologies, and performance optimization strategies
  • Translate complex data assets into actionable insights that drive measurable business improvements
• Healthcare & Pharmacy Solutions
  • Develop AI-driven solutions utilizing healthcare and pharmacy datasets, including Pharmacy claims, Clinical, Provider, Member, Formulary and utilization data
  • Architect solutions that improve, Medication adherence, Clinical quality outcomes, Member experience, Operational efficiency and Cost management
  • Work within highly regulated healthcare environments while ensuring compliance with privacy, security, and governance requirements
• Platform Engineering & AI Operations
  • Partner with platform, cloud, data engineering, and product teams to deploy scalable AI/ML systems
  • Lead adoption of MLOps, LLMOps, and AgentOps capabilities, including:
  • Prompt management
  • Model versioning
  • Experiment tracking
  • Automated evaluation
  • Monitoring and observability
  • CI/CD integration
  • Governance controls
• Establish frameworks for:
  • Drift detection
  • Performance monitoring
  • Incident response
  • Reliability management
  • Cost optimization
  • Build reusable libraries, APIs, accelerators, and shared AI services that support enterprise-wide adoption
• Responsible AI, Security & Governance
  • Ensure AI solutions comply with healthcare regulatory, privacy, and security requirements
  • Design and implement guardrails including - Prompt protection mechanisms, Tool access controls, Data protection and redaction, PHI-safe workflows, Auditability and traceability
  • Create transparent documentation covering model behavior, risks, limitations, controls, and mitigation strategies
  • Promote responsible AI practices throughout the solution lifecycle
  • Collaboration & Influence
  • Partner with executive leadership, business stakeholders, product organizations, and engineering teams to identify high-value AI opportunities
  • Influence enterprise AI strategy through technical expertise, innovation, and delivery excellence
  • Communicate complex technical concepts, architectural decisions, and analytical outcomes to both technical and non-technical audiences
  • Mentor and guide data scientists, engineers, and AI practitioners through technical leadership and best practices
  • Drive adoption through reusable artifacts, solution accelerators, reference implementations, and technical standards rather than direct people management
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelor's degree in Computer Science, Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or related discipline
• 14+ years of overall experience in Data Science, Artificial Intelligence, Advanced Analytics, or Machine Learning
• 7+ years of hands-on experience delivering production-grade AI/ML solutions in large enterprise
• Hands-on experience developing and deploying enterprise AI solutions using modern frameworks including: Scikit-learn, TensorFlow, PyTorch, LangChain, LangGraph, LlamaIndex, Vector Databases
• Solid experience working with enterprise LLM platforms such as Claude, OpenAI GPT/Codex, and equivalent technologies
• Experience with cloud-native AI platforms and distributed computing environments
• Solid proficiency in Python, SQL, and modern software engineering practices
• Demonstrated expertise across: Machine Learning, Deep Learning, Natural Language Processing, Generative AI, Agentic AI, Large Language Models, Advanced Analytics
• Proven expertise in Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, evaluation frameworks, and LLM safety mechanisms
• Demonstrated expertise in MLOps, LLMOps, and AgentOps practices
• Proven ability to architect, design, and deliver scalable AI solutions from ideation through production operations
• Proven excellent communication, stakeholder management, and technical leadership skills

Preferred Qualification:

• Master's degree or equivalent advanced experience

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.