Product Manager, Data Management & Platform

Essential Job Duties

Product-Led Data Strategy

• Contribute to and help execute the product vision and roadmap for HHAeXchange's enterprise data platform.
• Define how core clinical, operational, and financial data is modeled, linked, and surfaced across the product ecosystem.
• Partner with domain PMs (RCM, EHR, Payroll, Payments) to align data structures to real-world workflows and end-user needs.
• Identify opportunities to reduce data fragmentation and improve consistency across product domains.

AI Enablement & Innovation

• Serve as a product champion for AI and machine learning use cases built on the HHAeXchange data platform.
• Define and prioritize data requirements that enable AI-driven features including predictive analytics, anomaly detection, automation, and intelligent recommendations.
• Work with data science and engineering teams to ensure training data quality, feature pipelines, and model outputs are properly governed and trustworthy.
• Evaluate and recommend AI tools, platforms, and frameworks that can accelerate product delivery and enhance the platform's intelligence capabilities.
• Stay current on emerging AI/ML trends in healthcare — including generative AI, LLM applications, and agentic workflows — and translate relevant developments into product opportunities.
• Champion responsible AI practices, including fairness, explainability, and compliance considerations relevant to healthcare data.

Healthcare Data Enablement

• Ensure data models support claims, visits, authorizations, care plans, payroll, and payer rules.
• Translate regulatory, audit, and reimbursement requirements into data standards and traceability.
• Improve data lineage and reconciliation across payer-provider workflows.
• Support the development of a Universal Patient Record that is complete, current, and usable across the platform.

Cross-Team Execution

• Collaborate closely with Engineering, Architecture, and Platform teams to shape data services, APIs, and pipelines.
• Write clear product requirements, user stories, and acceptance criteria for data platform features.
• Prioritize data initiatives based on customer impact, revenue risk, compliance needs, and scalability.
• Drive alignment across product teams on shared data definitions, metrics, and reporting standards.

Governance & Data Quality

• Support the definition of data ownership, stewardship, and quality standards across product domains.
• Help establish validation, monitoring, and escalation processes for data defects.
• Create visibility into data health for product leaders, operations teams, and stakeholders.
• Contribute to documentation of data standards and governance policies.

Other Job Duties

Other duties as assigned by supervisor or HHAeXchange leader.

Travel Requirements

• Travel 10-25%, including overnight travel

Required Education, Experience, Certifications and Skills

Required 

5–7 years of experience in product management within healthcare IT, preferably in RCM, EHR, or payer-provider platforms.

Solid understanding of claims workflows, clinical documentation, authorizations, eligibility, and reimbursement processes.

Demonstrated interest in and experience with AI, machine learning, or advanced analytics applied to healthcare data.

Familiarity with data platforms, data warehouses or lakehouses, and analytics and reporting tools.

Ability to partner effectively with Engineering and Architecture on platform-level systems and data infrastructure.

Working knowledge of healthcare data regulations and compliance requirements (e.g., HIPAA, Medicaid program integrity, EVV).

Strong written and verbal communication skills, including the ability to translate technical data concepts for non-technical stakeholders.

Experience writing product requirements, managing a backlog, and driving delivery in an agile environment.

Curiosity, adaptability, and a proactive mindset in a fast-evolving product environment.

Preferred

Experience with AI/ML product development, including defining data pipelines, feature requirements, or model evaluation criteria.

Familiarity with generative AI tools and their application in healthcare workflows (e.g., clinical documentation, billing, analytics).

Experience with Medicaid home care, personal care services (PCS), or HCBS programs.

Knowledge of data governance frameworks, master data management (MDM), or data quality tooling.

Exposure to modern data stack technologies (e.g., dbt, Snowflake, Databricks, or similar).

Experience working with EVV data or similar real-time visit verification systems.

Familiarity with interoperability standards such as HL7, FHIR, or X12 EDI.




Success Measures (First 12–18 Months)

Clear, well-adopted data models across key clinical and financial workflows.

Measurable reduction in data-related defects impacting claims, payroll, and reporting.

At least one AI-driven product capability successfully launched on a trusted data foundation.

Improved reconciliation across payer, provider, and caregiver data.

Faster time-to-market for data-dependent product features.

Strong cross-team adoption of shared data standards and definitions.