About the position
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. Join our team at Optum Insight, where we are leveraging cutting-edge AI and machine learning technologies to revolutionize healthcare delivery, enhance customer engagement, and drive innovation across our digital platforms. This position offers a unique opportunity to lead the development of advanced analytics and ML solutions within Optum Insight’s Innovation portfolio. Digital Prior Authorization (DPA) is Optum Insight’s next-generation platform that aims to automate U.S. prior-auth decisions in real time. Its cloud-native data layer is the foundation powering MLOps, user experiences, reporting, benchmarking, and LLM observability. We are seeking a hands-on leader to own this data layer end-to-end and deliver the monitoring, auditability, and analytics required for trustworthy, scalable AI in healthcare. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges.
Responsibilities
- Own the product strategy, roadmap, and execution for DPA's shared data platform, spanning ingestion, curation, governance, lineage, and real-time APIs
- Define and deliver LLM & generative-AI observability (telemetry, drift detection, bias, safety, usage, cost) using Databricks, and modern LLM monitoring stacks
- Leverage AI tools to enhance productivity and innovation by streamlining workflows and automating repetitive tasks. Evaluate emerging trends to drive continuous improvement and strategic innovation
- Translate regulatory mandates (CMS, Da Vinci, HIPAA) into clear data, audit, and retention capabilities; ensure the platform enables end-to-end traceability
- Partner with engineering, architecture, security, and clinical SMEs to design scalable data models that serve MLOps pipelines, applications, BI/analytics, and external APIs
- Write clear requirements, OKRs, and user stories; prioritize backlog based on value, risk, and technical dependencies
- Establish and track KPIs such as data quality, SLA adherence and model-performance transparency
- Lead cross-team alignment, resolve blockers, and communicate progress to executives and matrix partners
- Champion a culture of rapid iteration, test-and-learn, and evidence-based decision making across product and engineering
Requirements
- 5+ years of product management with at least 3 years leading data-platform or analytics products in a SaaS or cloud environment
- 1+ years of experience in Demonstrated ownership of observability/monitoring capabilities for ML or LLM applications (e.g., latency, accuracy, bias, cost, compliance)
- Deep understanding of modern data architecture concepts (Lakehouse, Delta Lake, streaming, APIs, data contracts), and MLOps tools (Databricks, MLflow, LangChain, etc.)
- Proven success translating complex regulatory or clinical requirements into scalable product features
- Proven solid technical acumen; able to debate schema design, lineage strategies, and SRE metrics with engineers while articulating business value to non-technical stakeholders
- Proven track record of shipping products through Agile methodologies and influencing cross-functional teams without direct authority
- Proven excellent written and verbal communication skills; comfortable presenting to C-suite and external partners
Nice-to-haves
- Healthcare domain experience (payer, provider, EHR, Utilization Management, or interoperability standards such as FHIR, HL7, X12)
- Hands-on experience with Databricks Unity Catalog, Spark structured streaming, and Lakehouse-based governance frameworks
- Experience building external-facing data products or developer platforms (APIs, SDKs, self-service portals)
- Familiarity with AI safety, fairness, and audit frameworks
Benefits
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution
