Medisolv, Inc.

Compensation

Full Description

Job Description: • Build New Data Businesses • Identify unmet customer and market data needs beyond quality measure compliance (benchmarking, predictive, operational, financial performance). • Design and validate new monetization models: subscription data feeds, benchmarking indices, predictive insights, or performance dashboards. • Build prototypes and test directly with customers and partners (hospital, ACO, payer, life sciences). • Create pricing and business cases for each data offering — ARR potential, margin, scalability, and risk. • Partner with CFO and company/product strategy to tie each product to enterprise valuation levers. • Establish clear KPIs for adoption, retention, and incremental ARR contribution. • Conduct Jobs-to-Be-Done interviews and “wonder” sprints with Quality and Finance leaders to validate usefulness and willingness to pay. • Translate insights into technical requirements for Data Engineering and Legal teams. • Lead customer pilots with advisory partners to prove real-world value. • Collaborate with Product Marketing to define positioning, pricing, and launch assets for validated data products. • Drive initial sales enablement and customer case studies with early adopters. • Lead the articulation of Medisolv’s “data flywheel” — how our datasets create compounding advantage. Requirements: • Bachelor's degree in Business, Engineering, Marketing or related field (or equivalent experience). • 10+ years of experience in Product management, Product Marketing, Sales, or Marketing at healthcare SaaS/technology, product-driven companies. • Commercially-minded – fluent in pricing models and investor metrics. • Practical and customer-centric – grounded in real business problems facing quality and financial leaders in our target markets. • Technical and healthcare data fluency – strong understanding of clinical data, interoperability standards, APIs, FHIR data model and transport, data pipelines and de-identification methods. • Strategic translator – is effectively creating clarity from ambiguity, specifically connecting data science to business models. • Lean operator – runs fast with structured experiments and clear metrics. • Executive presence with excellent presentation, written, verbal skills. Benefits: • Health insurance • Professional development • Flexible work arrangements