Sr. Product Manager - AI & Data (Patient Experience & Commercial Operations Focus)

Natera is a global leader in cell-free DNA testing, dedicated to oncology, women’s health, and organ health. They are seeking a Senior Product Manager to lead the strategy and execution of data products and AI/ML systems focused on improving patient experience and operational efficiency. This role involves collaborating with various teams to identify bottlenecks and drive initiatives that enhance patient trust and operational effectiveness.

Responsibilities:

• Define and own the Data & AI product strategy and roadmap for the Patient Experience + Commercial Operations pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities
• Translate ambiguous business problems (e.g., stuck cases, fragmented patient communication, support inefficiencies) into clear product direction and measurable outcomes
• Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis
• Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc
• Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics
• Design and run experiments to validate product performance and measure causal impact
• Establish leading indicators and KPIs for proactive health assessments
• Partner with data and AI/ML engineering resources to deliver scalable products and capabilities
• Guide development of robust data pipelines and unified data models (360° views across key entities)
• Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining
• Ensure training–serving consistency, model versioning, and clear deployment decision gates
• Establish strong observability across data pipelines and models (data quality, latency, reliability, cost)
• Define and implement AI product patterns, including agentic workflows and RAG
• Establish evaluation frameworks for LLM-powered features (faithfulness, relevance, safety, cost, latency)
• Partner with engineering to implement prompt strategies, guardrails, and continuous evaluation pipelines
• Drive build vs. buy decisioning and proofs of concept
• Ensure data products meet regulatory and compliance requirements
• Champion data quality, lineage, and reliability through data contracts and observability standards
• Maintain strong documentation practices (e.g., model cards, dataset documentation, audit trails)
• Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly
• Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence
• Partner with stakeholders to integrate products into proactive, day-to-day decision-making
• Monitor product usage, performance, and business outcomes to iterate based on data and feedback
• Quantify and communicate impact (e.g., revenue lift, cost reduction, cycle time improvements, forecasting accuracy)
• Influence stakeholders across Patient Experience and Commercial Operations without direct authority

Requirements:

• 7–10+ years of product management experience, including 3+ years building data products, AI/ML systems, or related platforms
• Demonstrated domain fluency in Patient Experience and Commercial Operations
• Strong understanding of patient journeys, support channels (e.g., chat, voice, call centers), and operational workflows that drive conversion and test completion
• Familiarity with key domain-relevant tooling (e.g., patient portals and support platforms) and associated data
• Strong technical acumen (e.g., querying data, working in notebooks for EDA and experimentation, modeling datasets)
• ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift)
• Experience shipping LLM-powered or AI products (prompting, RAG, evaluation frameworks, guardrails)
• Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster)
• Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams
• Experience working in regulated environments (e.g., healthcare, life sciences, fintech)
• Advanced degree in a technical and/or business discipline
• Experience in healthcare, diagnostics, life sciences, and/or digital health
• Familiarity with healthcare data domains and systems, including patient, provider, payer, claims, billing, and clinical trial data
• Experience with vendor evaluation, platform selection, or external AI tooling ecosystems