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Nelly is building an AI-driven financial operating system for European healthcare. This Staff Product Manager role owns the hardest problems in the data and integration platform that underpins all Nelly products—from documentation to billing to payments.
You will own the strategy, metrics, and roadmap for data and integration challenges across the entire platform lifecycle: how practice data leaves a practice management system, through ingestion and modeling, to the products that depend on it. Your scope spans multiple teams and extends to product-wide architectural questions.
Key responsibilities include:
- Defining the core data model that all products rely on (patients, appointments, treatment plans, invoices, etc.), including ownership, freshness, reliability, and regulatory compliance (GDPR, health-data regulations)
- Shaping how partners connect to Nelly through the External API to serve practices on any system and open new markets beyond Germany
- Making data and integration quality measurable and visible; practices experience silent failures before we detect them
- Holding an end-to-end model of the platform and serving as a credible technical partner to engineering on architecture and trade-offs
- Driving business outcomes: naming the metric each project moves and letting evidence drive prioritization
The problem space is substantial: Nelly integrates with dozens of practice management systems, each with different data models and interfaces. Success depends on answering four core questions: Can we connect? Can we read and write deeply enough? Is the data quality acceptable? Can every product and team easily build on it?
You will work in a high-velocity, talent-dense environment where you move fast, make bold but reversible decisions, and challenge directly—including upward. The company is Series B funded (€50M+) and expanding rapidly across Europe.
Requirements:
- 7+ years of product management experience
- Agency: you pursue problems that matter most, beyond immediate scope
- Comfort in high-velocity environments; ability to make bold calls and challenge early
- Business-outcome orientation; data-driven prioritization
- Technical fluency: confident reasoning about APIs, data models, data flows, and system architecture; credible partner to senior engineers
- Daily use of AI to prototype, analyze, spec, and ship small features independently
Preferred qualifications:
- Experience building and shipping AI products
- Background in data platforms or data products
- B2B SaaS experience in healthcare or other regulated industries
- Professional German language knowledge
