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.

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