Company Overview: We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.

Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech.

We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.

Role Overview: Protege’s healthcare product success function sits at the intersection of scientific innovation, operational execution, and customer delivery.

We’re looking for a Head of Product Success (Healthcare) who can bridge the gap between our Data Lab’s deep innovation work and the operational realities of delivering and refining healthcare data products at scale.

You’ll lead a team of technical account managers and applied data scientists who make complex multimodal datasets (EHR, imaging, claims, etc.) usable and deliverable for AI model development while surfacing insights that from customer use that guide product development

You’ll need to think like a scientist, operate like an executive, and lead like a builder — translating brilliant, bespoke data ideas into repeatable, scalable delivery systems that serve AI developers’ real-world needs.

Key Responsibilities: Operationalize Scientific Innovation

• Work closely with Protege’s Head of Product & Data Labs to translate complex scientific methodologies into scalable, customer-ready workflows
• Apply the 80/20 rule — knowing when a process needs perfection and when it needs to move
• Identify and document best practices for multimodal data feasibility, joining, and de-identification

Lead and Develop a High-Performing Team

• Manage a team of Technical Account Managers and applied data scientists
• Build a culture of rigor and delivery — scientific enough to be credible, but pragmatic enough to move fast
• Develop onboarding, documentation, and repeatable playbooks for healthcare data feasibility and delivery

Bridge Science, Product, and Customers

• Collaborate with the CSO, Head of Product, and Platform teams to align internal feasibility and delivery capabilities with customer use cases
• Ensure Protege’s data products meet the expectations of healthcare AI builders — fit-for-purpose data, transparency, and reproducibility
• Delight Protege’s customers by exceeding their expectations; being a driving force for repeat business

Drive Operational Excellence

• Design and own healthcare delivery SLAs, QA standards, and throughput metrics
• Introduce tooling and process automation to scale delivery capacity
• Hold the line on execution, even amid scientific ambiguity or evolving requirements

Be a Credible Voice Across Domains

• Serve as both translator and challenger to scientific leadership — ensuring innovation moves toward scalability
• Represent Protege with partners and customers who are developing healthcare AI models and need data that “just works”

About You:

• 7–10 years of experience in healthcare data, product delivery, or data science operations
• Strong grasp of AI data needs — you understand how model developers think about data quality, coverage, and bias
• Demonstrated success leading operationally excellent technical teams
• Able to translate scientific complexity into scalable systems without losing rigor
• Confident engaging with PhD-level scientists and senior executives; you can debate ideas without ego
• Thrives in ambiguity, drives toward clarity, and keeps teams grounded in delivery

Bonus:

• PhD or advanced technical degree in a healthcare, quantitative, or data science field
• Experience managing large, multimodal healthcare datasets or leading data curation for AI/ML applications
• Exposure to regulatory frameworks (HIPAA, expert determination, de-identification)
• Deep understanding of healthcare data modalities (EHR, imaging, claims, genomics, etc.) and de-identification workflows

Why Protege

• Shape the foundation for how healthcare data is delivered for AI innovation
• Work alongside top scientific and product talent tackling one of AI’s hardest problems
• Build and lead a team that makes innovation scale
• Competitive compensation, equity, and benefits package