Description

Job Description - Director / Senior Director, Technical Product Management

Data Platform & AI Products | Remote | Full-Time
About The Position:

Norstella is seeking a Director or Senior Director of Technical Product Management to lead the strategy and execution of our data platform and AI-powered product suite. This is a high-impact, cross-functional role at the intersection of commercial life sciences data, modern AI delivery mechanisms, and revenue growth, sitting within a global product and technology organization. The right candidate is equally comfortable whiteboarding architecture with engineers and conducting discovery sessions with enterprise customers.
Key Responsibilities:

Product Strategy & Roadmap
• Own the end-to-end product vision and roadmap for our data platform, including data delivery mechanisms - APIs, MCPs, data feeds, and AI agents.
• Define and execute go-to-market strategy for AI-native products built on commercial life sciences data assets (open claims, EMR notes, payer data, and more).
• Prioritize features and capabilities based on market demand, competitive landscape, and revenue impact.
• Translate complex data and AI capabilities into clear, differentiated value propositions for commercial and clinical customers.

AI & Data Platform Delivery
• Oversee the product lifecycle for AI-native capabilities including agentic workflows, LLM-powered insights, and structured/unstructured data pipelines.
• Drive adoption of modern data delivery modalities: RESTful APIs, MCP (Model Context Protocol) servers, bulk data feeds, and embedded AI agents.
• Collaborate with data science, engineering, and architecture teams to ensure platform scalability, data quality, and compliance.
• Stay ahead of the AI/ML landscape to identify emerging patterns applicable to life sciences commercialization.

Revenue & Commercial Focus
• Partner closely with sales, solutions engineering, and customer success to drive pipeline expansion, accelerate deal cycles, and support renewals.
• Serve as a subject matter expert and executive-level product voice in strategic customer conversations.
• Build credibility with technical buyers by demonstrating hands-on fluency with data schemas, API design, and AI/ML delivery patterns.
• Partner with sales and customer success in executive business reviews, QBRs, and strategic account planning sessions.
• Define and track product-level KPIs tied to revenue growth, adoption, and retention.

Leadership & Cross-Functional Collaboration
• Manage and mentor a team of product managers; establish a culture of curiosity, rigor, and customer empathy.
• Align product priorities with business objectives through regular engagement with executive leadership.
• Coordinate across data operations, legal/compliance, marketing, and technology to ship high-quality products on schedule.
• Communicate roadmap and progress clearly to both technical and non-technical stakeholders.
Required Qualifications
• 10-15 years of product management experience, with meaningful time in data platforms, health/life sciences, or enterprise SaaS.
• Experience building and commercializing AI-native products - from concept through launch and revenue generation.
• Deep familiarity with commercial life sciences data assets, including open/closed medical and pharmacy claims, EMR/EHR notes, payer formulary and coverage data, and provider/patient-level datasets.
• Strong technical fluency: able to engage credibly with engineers on API design, data schemas, LLM pipelines, and agent frameworks without writing code.
• Experience owning data delivery products - APIs, data feeds, MCP servers, AI agents, or similar developer-facing surfaces.
• Demonstrated ability to run structured customer discovery across both technical (engineering, data science) and business (commercial, clinical, operations) stakeholders.
• Revenue orientation - experience tying product decisions to ARR, expansion, and churn metrics.
• Excellent written and verbal communication; can tailor messaging from data engineer to chief commercial officer.
Preferred Qualifications
• Experience at a health data company, payer analytics firm, or life sciences technology vendor.
• Familiarity with Model Context Protocol (MCP), LangChain/LangGraph, or similar agentic AI frameworks.
• Background in FHIR, HL7, or other healthcare interoperability standards.
• MBA or advanced degree in a quantitative or life sciences field.
• Occasional travel may be required.