In addition to working in accordance with appropriate conduct and behavioral standards, specific responsibilities of this role include:

Product Vision and Strategy

• Own the product vision, strategy, and multi-quarter roadmap for Nextech's reporting, analytics, and AI-driven insights portfolio across financial and clinical domains.
• Set direction in ambiguity by making clear, defensible bets on where to invest, what to sequence, and what to decline, grounded in client value and business impact.
• Define the analytics and insights strategy that positions Nextech ahead of client and market needs, including the shift toward proactive, AI-driven insight.
• Prioritize and manage the portfolio backlog, making data-driven tradeoffs on scope, sequencing, and risk.
• Ensure responsible and compliant use of AI and client data aligned with regulatory and company standards.

Modern Data Architecture and Analytics Platform

• Work closely with Data Engineering to understand how data is constructed across the lakehouse's medallion layers, moving from raw ingestion (bronze) to cleansed and conformed data (silver) to curated, analytics-ready data products (gold), then translate that understanding into sound product decisions and tradeoffs.
• Help shape the broader data foundation that powers reporting and AI-driven insights, including the data warehouse and data marts, ELT/ETL pipelines, semantic and metrics layers, and embedded analytics.
• Translate a modern data architecture vision into a product roadmap that scales across specialties and clients.
• Make informed tradeoffs on data modeling, latency, governance, and reusability that balance speed to value against long-term platform health.
• Champion data quality, lineage, and trust as first-class product outcomes, since analytics is only as valuable as the data beneath it.

Discovery and Client Insight

• Drive continuous, structured discovery with providers, practice administrators, revenue cycle leaders, and clinical staff to validate needs, financial and clinical use cases, and willingness to pay.
• Run discovery at pace, converting client learning into clear, actionable decisions the delivery team can execute quickly, rather than open-ended research.
• Synthesize qualitative and quantitative signal into a sharp, defensible point of view on what to build and why.
• Validate direction early and often through prototypes, pilots, and design partners to reduce delivery risk.

Requirements Definition and Engineering Partnership

• Author clear, crisp, and unambiguous product requirements (outcomes, epics, user stories, acceptance criteria, and workflow documentation) that engineering and design can act on without guesswork.
• Demonstrate extreme ownership in driving product refinement alongside engineering counterparts, staying in the details from definition through delivery.
• Partner deeply with engineering on technical tradeoffs, data dependencies, and sequencing, resolving ambiguity before it becomes rework.
• Maintain a healthy, well-groomed backlog that keeps the delivery team moving at a predictable pace.

Execution, Delivery, and Team Leadership

• Lead cross-functional execution to deliver high-quality reporting and analytics capabilities in iterative, value-driven releases.
• Galvanize engineering and design teams around a shared vision, creating the clarity, momentum, and urgency that drive fast, quality delivery.
• Operate as a force multiplier by removing blockers, managing dependencies, and raising the bar on craft across the teams you influence.
• Model and mentor strong product practices, elevating the discovery, definition, and delivery discipline of the broader product team.

Metrics, Business Impact, and Commercial Success

• Define, track, and report on the financial and clinical KPIs that matter in non-acute healthcare, including revenue cycle performance, charge capture and charge lag, accounts receivable aging, denials and net collection rate, underpayment detection, and clinical quality and operational measures.
• Tie product outcomes to measurable client and business impact, including adoption, retention, revenue, and efficiency gains.
• Partner with Commercial teams on positioning, packaging, launch, and adoption strategies for reporting and analytics offerings.
• Use data and market insight to guide prioritization and continuously assess product-market fit.
• Additional duties as required.

• 6+ years of product management experience, including significant time owning reporting, analytics, or data-driven products.
• • Demonstrated fluency in financial outcomes and KPIs in non-acute, ambulatory, or specialty healthcare, including revenue cycle management, charge capture, accounts receivable aging, denials, net collection rate, and underpayment detection.
  • Proven track record of delivering measurable results in fast-paced, high-growth environments.
  • Working knowledge of modern data architecture, including the data warehouse and data marts, ELT/ETL pipelines, semantic and metrics layers, and embedded business intelligence, and how it enables analytics and AI-driven insights.
  • Conversant in data lake and lakehouse architecture and the medallion model of refining data from raw ingestion (bronze) to cleansed, conformed data (silver) to curated, analytics-ready products (gold). Must understand how the data is constructed well enough to partner with engineering on design tradeoffs. This is a step beyond domain or subject-matter expertise, though it does not require hands-on data engineering.
  • Demonstrated extreme ownership in authoring crisp product requirements and driving refinement in close partnership with engineering.
  • Proven ability to run rapid client discovery that produces clear, actionable decisions for delivery teams.
  • Strong understanding of AI and machine learning concepts as applied to analytics and insight generation.
  • Demonstrated ability to galvanize engineering and design teams and influence cross-functionally without direct authority.
  • Experience working in Agile environments (backlog management, sprint planning, roadmap development).
  • Strong analytical, written, and

• SQL fundamentals: strong, working command of SELECT, WHERE, JOIN, GROUP BY, HAVING, and ORDER BY, sufficient to query data and answer questions independently rather than waiting on an analyst.
• Relational database fundamentals: a solid grasp of tables, keys, relationships, and normalization basics.
• Demonstrated hands-on experience implementing agentic AI product workflows that execute multi-step tasks, with mandatory guardrails including human approval checkpoints on generated content.
• A proven track record of adopting and leveraging AI in day-to-day work, not simply a willingness to learn it. This role calls for an active adopter who builds AI into how they operate and helps the team do the same.