Senior Product Owner, Clinical Claims & Grouper Solutions (Chicago)
Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. Please visit Fractal | Intelligence for Imagination for more information about Fractal Role Overview Fractal is seeking a Senior Product Owner for Clinical Claims & Grouper Solutions. This is for a clinical claims data product to support healthcare payer clients in modernizing clinical claims data products, medical grouper capabilities, and claims classification workflows. This is a client-facing functional role for someone with strong experience in payer claims, healthcare coding, medical groupers, claims analytics, medical economics, payment integrity, actuarial analytics, or healthcare data product delivery. The role will partner with business, clinical, actuarial, claims, analytics, data engineering, and AI/ML teams to define requirements, validate outputs, assess downstream impacts, and support adoption readiness for modernized clinical claims data products. The candidate must understand how claims data and clinical coding translate into grouped outputs that drive payer workflows and analytics. This includes how claims classification supports cost and utilization analysis, medical economics, actuarial reporting, operational workflows, clinical programs, and broader business decision-making. This person is not expected to be a hands-on data scientist or engineer but must be able to partner effectively with technical teams and bring strong payer claims / medical grouper domain judgment. What You’ll Do Discovery, Current-State Assessment, and Workflow Mapping Lead discovery workshops 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 that depend on grouper, service category, or claims classification outputs. Requirements Specification and Clinical Claims Data Product Architecture 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 claim types such as inpatient, outpatient, professional, ancillary, and pharmacy/Rx. 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, interfaces, and data quality expectations. Ensure claims classification and service category outputs are traceable, testable, explainable, auditable, versioned, and aligned to business outcomes. Baseline Comparison, Validation, and Migration Readiness Support baseline-to-target output comparison, parallel validation, variance analysis, business impact assessment, and migration readiness planning. Help 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. AI/ML Collaboration and Product Modernization Partner with AI architects, data scientists, and engineers to identify where deterministic rules, configurable business logic, and AI/ML-enabled capabilities can each add value. Help 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. Stakeholder Alignment and Governance 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 in partnership with client business owners. Help clients move toward transparent, governed, explainable, and analytically useful clinical claims data products. What You’ll Bring 8 years of experience in healthcare payer claims, claims analytics, medical economics, payment integrity, actuarial analytics, clinical coding, payer technology, healthcare consulting, or healthcare data product delivery. Hands-on experience with medical groupers, claims classification, service category logic, claims editing, payment integrity, clinical claims analytics, or payer claims rule logic. Familiarity with commercial or industry grouper / claims solutions such as Milliman, MedInsight, HCG-style service categories, Solventum/3M, Optum/Change Healthcare, Cotiviti, CMS grouping logic, DRG/APC/OPPS workflows, or similar platforms. Strong understanding of payer claims data at both claim header and line level. Familiarity with healthcare coding and billing concepts such as ICD-10, CPT, HCPCS, revenue codes, DRG/APC, modifiers, place of service, bill type, NCCI/MUE, and 837/835 claims data. Understanding of how grouped claims data supports total cost of care measurement, utilization benchmarking, actuarial reporting, medical economics, provider performance, risk adjustment, value-based care, and cost driver analysis. Experience facilitating workshops with business, clinical, actuarial, claims, compliance, operations, analytics, and technology stakeholders. Ability to create high-quality BRDs, user stories, business rules, decision tables, process maps, source-to-target mappings, acceptance criteria, test scenarios, and validation documentation. Experience with baseline-to-target comparisons, UAT, parallel testing, variance analysis, business impact assessment, or migration readiness planning. Ability to translate complex payer domain concepts into actionable requirements for engineering, data, and AI/ML teams. Strong analytical, facilitation, communication, and consulting skills. Preferred 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. You May Be a Fit If You Come From A healthcare payer medical economics, payment integrity, claims analytics, actuarial, clinical policy, provider analytics, value-based care, o
