Director, Data & Analytics Products

AdvancedMD

9h•Hybrid

About The Position

AdvancedMD is a unified cloud suite of medical office software hosted on Amazon Web Services/AWS including practice management, electronic health records, and patient engagement, and offers managed medical billing services for independent practices. AdvancedMD serves an expansive national footprint of 65,000 practitioners across 14,000 practices and 900 independent medical billing companies. 8.8M insurance claims are processed every month on the AdvancedMD billing platform! Role Summary Are you a product-driven data leader who thrives at the intersection of analytics, AI, and business decision-making? We are seeking a Director, Data & Analytics Products to own the strategy, roadmap, and delivery of enterprise data and analytics offerings. In this role, you will champion data as a product, ensuring insights are trusted, actionable, and deliver measurable business value. You will define how data products are designed, governed, and delivered across the organization—treating data not only as a foundational platform, but also as a scalable commercial asset. Partnering closely with Product, Engineering, AI, Finance, Legal, and Go-to-Market teams, you will lead the development of analytics products that improve understanding, enable decision support, and unlock monetization opportunities. This is a highly cross-functional leadership role for a strategic yet execution-oriented product leader who can balance analytics rigor with real-world impact—ensuring data products are not just built, but used, trusted, and value-creating.

Requirements

Bachelor's or Master’s degree in Computer Science, Engineering, Data Science, or related field
8+ years leading data, analytics, product management, or data platforms, with demonstrated leadership responsibility
Proven experience treating data as a product, not just a reporting or BI function
Experience defining, launching, and scaling analytics or data products (e.g., dashboards, benchmarks, insights, datasets, APIs)
Strong understanding of modern data platforms, analytics tools, and data governance principles
Experience partnering cross-functionally with Product, Engineering, Finance, Legal, Sales, and Marketing
Ability to translate complex data and technical concepts into clear customer and business value
Foundational knowledge and experience around the data domain
Proven ability to define, prioritize, and deliver complex technical products
Strong analytical, communication, and stakeholder management skills
Strong knowledge of Agile principles and product delivery processes
Demonstrated track record of delivering products on time and driving measurable business value
In-depth understanding of industry market conditions and trends
Creative and innovative thinker

Nice To Haves

Experience leading or contributing to data monetization initiatives, including packaging, pricing, or go-to-market pilots
Familiarity with AI/ML-enabled products and the data requirements that power intelligent experiences
Experience in healthcare, health tech, SaaS, or regulated industries
Background working with enterprise-scale data platforms (e.g., cloud data warehouses, embedded analytics)
Experience building and mentoring product-minded data or analytics teams
Background in software engineering or data engineering
Experience working in regulated industries (e.g., healthcare, finance)

Responsibilities

Own the product strategy and roadmap for data, analytics, and monetization, balancing internal insight needs with external commercial opportunities
Define, launch, and scale data products including dashboards, benchmarks, insights, datasets, and APIs
Deliver decision-oriented analytics that explain performance, drivers, and outcomes—not just reports
Lead data monetization strategy and pilots, including packaging, pricing concepts, and validation of customer demand
Partner with Finance, Legal, Sales, and Marketing to ensure data offerings are compliant, viable, and scalable
Ensure data products are reusable, consistent, and aligned to enterprise data standards
Collaborate with AI and Engineering teams to enable AI initiatives through high-quality, well-governed data assets
Communicate roadmap priorities, progress, risks, and tradeoffs clearly to stakeholders and leadership
Build and mentor a product-minded data and analytics team