Product Manager

Hospital for Special Surgery•New York, NY

8d•$101,500 - $154,750

About The Position

The Product Manager will work in HSS’s Transformation Office (Atlas) and Enterprise Data & Analytics organization, building data and AI products that improve internal care delivery and organizational performance and turn HSS clinical expertise and intellectual property into commercial B2B and B2C offerings. The role owns products end to end, from problem definition and discovery through prototyping, development, launch, adoption, and iteration. It leads a matrixed Product-Oriented Delivery team of engineers, designers, analysts, and domain experts, and helps shape how product work is done in an AI-native organization. The Product Manager is expected to prototype directly using AI coding agents and low-code tools, work within git-based software development workflows, partner on trusted data foundations, and connect insights to decisions, improved workflows, and measurable value. The position also contributes to market discovery and commercialization, applies responsible AI and healthcare data governance practices, and builds reusable systems and workflows that increase team effectiveness.

Requirements

Bachelor's degree or equivalent experience.
At least 8 years of experience in product management, data, AI, technology, digital transformation, or a related field, including delivery of solutions across multiple technologies and business functions.
Daily hands-on use of AI tools, including AI coding agents to produce working prototypes, with a portfolio of things built.
Working knowledge of git and GitHub, including branches, pull requests, and code review, and of the software development lifecycle.
Strong SQL skills and working knowledge of data modeling concepts, including table grain, dimensional models, medallion architecture, data quality, and lineage.
Strong understanding of modern data and AI capabilities, including generative AI, LLM-based tools, agentic workflows, data products, and analytics.
Evidence of a bias toward action, including shipping quickly, learning from users, and iterating rather than over-planning.
Ability to lead and influence a cross-functional, matrixed team without direct authority.
Awareness of responsible AI practices and healthcare data privacy and governance requirements, such as HIPAA and PHI.
Exceptional communication and storytelling skills, including the ability to translate technical concepts for engineers and senior leaders.
Comfort operating in a fast-moving environment where priorities evolve and progress depends on learning and iteration.

Nice To Haves

Experience with Databricks and AI coding agents such as Claude Code, Cursor, or Codex.
Experience with Python APIs.
Experience building or launching B2B SaaS or consumer products.
Experience in healthcare or another regulated environment.

Responsibilities

Own the full lifecycle of one or more data and AI products, from problem definition and discovery through prototyping, development, launch, adoption, and iteration.
Lead a matrixed Product-Oriented Delivery team of engineers, designers, analysts, and domain experts; set direction, guide work, and drive decisions toward shipped outcomes.
Build working prototypes using AI coding agents and low-code tools to test assumptions with users quickly.
Work within the team's software development lifecycle by writing requirements and acceptance criteria, managing work in git-based workflows, reviewing pull requests for product intent, and contributing small changes when useful.
Partner with data engineers on data models, data quality, lineage, and semantic and metric layers so products are accurate and trusted.
Shape B2B and B2C products based on HSS intellectual property by conducting customer and market discovery, analyzing competitors, and contributing to go-to-market, pricing, and packaging recommendations.
Track developments in generative AI, agentic AI, and data platforms and translate them into product opportunities and changes to team practices.
Build reusable agent workflows, prompt libraries, product templates, and automated reporting, and teach teammates to use them.
Apply responsible AI and data governance practices, including evaluation, guardrails, and HIPAA-aligned handling of protected health information.
Communicate decisions, trade-offs, and results clearly to stakeholders and leaders, explaining the story behind the data.
Own at least one product area within a POD and be accountable for its outcomes.
Bring ideas to working prototypes in front of real users within days, ship one to two validated major releases per quarter with adoption or impact metrics, and build a reusable AI workflow or system adopted by the team.