Senior Product Owner, Clinical Claims & Grouper Solutions

Fractal Analytics is seeking a Senior Product Owner to lead client-facing product discovery and requirements for a clinical claims data product. The role focuses on modernizing clinical claims data products, medical grouper capabilities, and claims classification workflows for healthcare payer clients, while partnering closely with business and technical teams to validate outputs and support adoption readiness.

Role Overview

This is a functional, client-facing role centered on clinical claims data, grouped outputs, and the workflows that depend on them. You will partner with business, clinical, actuarial, claims, analytics, data engineering, and AI/ML teams to define requirements, validate outputs, assess downstream impacts, and ensure adoption readiness for modernized clinical claims data products.

The position requires domain judgment across payer claims and medical grouper concepts. While the role is not expected to be hands-on in data science or engineering, you must be able to collaborate effectively with technical teams and translate clinical and claims coding into grouped outputs that support payer workflows and analytics.

Key Responsibilities

• Lead discovery, current-state assessment, and workflow mapping with payer business, clinical, coding, actuarial, claims operations, compliance, analytics, data science, and technology stakeholders.
• Document current-state claims classification and grouper usage, including business workflows, data inputs, outputs, pain points, downstream dependencies, and analytics use cases.
• Map how claims classification outputs are used across medical economics, actuarial reporting, cost-of-care analysis, utilization benchmarking, provider analytics, payment integrity, claims operations, care management, clinical policy, finance, quality, value-based care, and executive reporting.
• Identify major reports, dashboards, models, workflows, and business decisions dependent on grouper, service category, or claims classification outputs.
• Translate payer claims, coding, clinical policy, operational, actuarial, medical economics, and analytics needs into BRDs, user stories, process maps, decision logic, business rules, acceptance criteria, and validation documentation.
• Define requirements for clinical claims data products across inpatient, outpatient, professional, ancillary, and pharmacy/Rx claim types.
• Support design and validation of service category frameworks used for cost, utilization, benchmarking, reporting, and downstream analytics.
• Partner with technical teams to define data inputs, outputs, source-to-target mappings, validation rules, and data quality expectations.
• Ensure claims classification and service category outputs are traceable, testable, explainable, auditable, versioned, and aligned to business outcomes.
• Support baseline-to-target output comparison, parallel validation, variance analysis, business impact assessment, and migration readiness planning.
• Define what “ready for adoption” means for each business use case, including accuracy, explainability, financial impact, operational impact, reporting continuity, trend stability, and stakeholder sign-off.
• Evaluate impact on downstream analytics such as cost-of-care reporting, utilization benchmarks, actuarial trend, PMPM reporting, provider analytics, value-based care performance, clinical program analytics, and executive dashboards.
• Support UAT planning, gold-standard test case definition, regression testing, dual-run reporting, stakeholder communications, and production transition planning.
• Partner with AI architects, data scientists, and engineers to identify where deterministic rules, configurable business logic, and AI/ML-enabled capabilities add value.
• Distinguish which claims classification logic must remain rules-based and auditable versus where machine learning, model-assisted, or GenAI-enabled capabilities may improve usability, validation, anomaly detection, policy interpretation, variance triage, test generation, or insight generation.
• Ensure AI/ML opportunities are grounded in payer workflows and do not compromise explainability, compliance, governance, or business trust.
• Facilitate alignment across business, clinical, actuarial, claims, compliance, analytics, data science, and technology stakeholders.
• Help establish governance for code sets, service categories, clinical logic, business rules, versioning, output definitions, benchmarks, and downstream data product usage.
• Support adoption readiness, stakeholder communications, and production transition planning with client business owners.

What Success Looks Like

• Build trust with payer business, clinical, coding, actuarial, claims, analytics, compliance, and technology stakeholders.
• Explain how claims classification, service categories, and grouper outputs affect payer workflows, analytics, reporting, financial analysis, and operational decisions.
• Connect grouper outputs to broader business outcomes including total cost of care, utilization benchmarking, actuarial trend, provider performance, value-based care, risk adjustment, and cost driver analysis.
• Convert complex clinical, coding, actuarial, claims, and workflow logic into clear business and technical requirements.
• Define a practical framework for evaluating baseline versus target grouper or claims classification outputs.
• Identify major downstream reports, models, dashboards, workflows, and decisions that depend on claims classification or service category data.
• Explain output variances in business, coding, clinical, actuarial, financial, and technical terms.
• Help clients move toward modern, transparent, governed, and analytically useful clinical claims data products.

Required Experience

• Experience working for or with a Medicaid, Medicare Advantage, commercial payer, Blue plan, employer group analytics, or payer technology organization.
• Experience with medical economics, actuarial trend, total cost of care, utilization benchmarking, risk adjustment, provider performance, value-based care, utilization management, or clinical program analytics.
• Experience evaluating or migrating legacy grouper outputs, claims engines, payment integrity platforms, analytics data marts, service category frameworks, or other payer claims data products.
• Familiarity with AI/ML or GenAI use cases in payer claims, payment integrity, utilization management, medical policy, test generation, semantic search, anomaly detection, cost driver identification, or explainable analytics.
• Experience supporting dual-run reporting, bridge tables, crosswalks, impact analysis, stakeholder adoption, cutover, or production stabilization.
• Experience with Jira, Confluence, Azure DevOps, SQL, data dictionaries, claims data warehouses, Databricks, Power BI, Facets, QNXT, Edifecs, or healthcare analytics platforms.
• Healthcare coding, clinical, actuarial, or health information credentials such as CPC, CCS, RHIA, RHIT, CIC, COC, CPMA, CRC, RN, MPH, MHA, ASA, or FSA are a plus.

Technologies

• Jira, Confluence, Azure DevOps
• SQL, Databricks, Power BI
• Facets, QNXT, Edifecs
• BRDs, user stories, UAT, PMPM

Location

California (onsite)

Compensation

USD 170,000 - 200,000 per yearly.

In addition, for the current performance period, you may be eligible for a discretionary bonus.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• Life insurance
• Disability plans
• Eligible for benefits on the first day of employment with the Company
• 401(k) Plan eligibility after 30 days of employment
• 11 paid holidays
• 12 weeks of Parental Leave
• “free time” PTO policy